Table of Contents
What you should know right away
ARP spoofing is a form of Man-in-the-Middle attack – an attack in which an attacker intercepts and controls communication between hosts in a local network (LAN).
The attack mechanism is based on sending forged ARP packets that introduce incorrect entries into the ARP tables of devices. As a result, network traffic is delivered to the attacker instead of the legitimate destination.
The most characteristic symptom is an address conflict – the same MAC address becomes assigned to two different IP addresses (for example, a gateway and a workstation).
Detecting the attack is possible thanks to network traffic analysis and monitoring anomalies in ARP communication, such as duplicated MAC addresses or an unusual volume of ARP traffic.
Protection against ARP poisoning is based on three pillars:
Encrypting transmissions (HTTPS, SSH, VPN) – even if traffic is intercepted, the data remains unreadable.
Advanced switch features, such as Dynamic ARP Inspection (DAI) and Port Security, which block forged ARP packets.
Continuous network monitoring, which allows irregularities to be detected in real time.
Typical symptoms and reactions – in brief
| Symptom in the LAN | What it may indicate | Recommended action |
|---|---|---|
| The same MAC address assigned to two IPs | Possible ARP poisoning or incorrect configuration | Verify the ARP table and monitor duplicates in a network traffic analysis tool |
| Increase in the number of ARP packets in a short time | Attempt to impersonate multiple devices | Check the traffic sources and enable alerts in the monitoring system |
| No response from devices / loss of connectivity | DoS attack caused by incorrect address mapping | Restore correct ARP entries, isolate the device with the suspicious MAC |
| Unusual transmission delays | Man-in-the-Middle attack – traffic passes through an additional point | Analyse the packet path and identify the intermediary |
Attacks such as ARP spoofing are not always visible at first glance. Their strength lies in their simplicity and in the fact that they exploit the basic trust between devices in a network.
The only effective way to detect and neutralize a Man-in-the-Middle attack is proactive network traffic analysis, supported by continuous monitoring and automatic alerts for address conflicts.
What is ARP spoofing and why is it so dangerous?
What is the ARP protocol — a simple comparison
The ARP protocol (Address Resolution Protocol) works in a local network like a phone book — it translates logical addresses (IP) into physical addresses (MAC). When host A wants to send a frame to host B in the same subnet, it asks: “Who has IP X.X.X.X? Send your MAC.” The recipient replies, and the sender stores the IP↔MAC relation in the local ARP table. Thanks to this, subsequent packets go directly to the correct device.
Key characteristics of ARP:
it operates on layers 2/3 of the OSI model;
it is stateless and simple — requests and replies are neither signed nor authenticated;
ARP entries are usually stored temporarily and refreshed periodically.
This simplicity facilitates communication but also creates a weakness that attackers can exploit.
How ARP poisoning works
ARP poisoning consists of sending forged ARP replies to one or more hosts in order to enforce incorrect IP→MAC mapping. An attacker can, for example:
send a reply to computer A claiming that “the gateway 192.168.1.1 has MAC aa:bb:cc:dd:ee:ff” — where aa:bb… is the attacker’s MAC;
simultaneously send a reply to the gateway claiming that “computer A has MAC aa:bb:cc:dd:ee:ff”.
The effect: both computer A and the gateway store in their ARP tables that traffic to the other side should be sent through the attacker’s MAC. From that moment, the attacker receives traffic from both sides and can:
forward it unchanged (transparent eavesdropping),
modify it (injection, content replacement),
block it (local DoS).
In practice, the attack is executed using tools that automatically send sequences of forged ARP replies at a defined interval to continually maintain the “poisoned” entries in victims’ ARP tables.
Why does this work at all? — weaknesses of the ARP protocol
The reason ARP spoofing is effective lies in the design of ARP — the protocol was created with an assumption of trust within the LAN. ARP:
does not verify where a reply originates from;
accepts the first response it encounters and stores it in the table;
does not use cryptographic mechanisms or signatures.
Additionally, typical operating systems and network devices update ARP entries without additional validation — they accept “gratuitous ARP” or overwrite existing entries with new data. This makes the attack fast and effective, often without visible symptoms at the user application level.
Connection to a Man-in-the-Middle attack
The goal of ARP spoofing is usually to assume the role of an intermediary, meaning to perform a Man-in-the-Middle attack. The difference lies in the level and method of stepping between communication endpoints:
A Man-in-the-Middle attack is a broader concept — it describes a situation where an attacker controls data transfer between two parties and can eavesdrop or modify data.
ARP spoofing is a technique for obtaining such a position inside a LAN.
Consequences once the attacker becomes the intermediary:
data transmitted without encryption becomes readable;
sessions authenticated with one-time cookies or tokens can be hijacked;
the victim does not have to notice any change in the appearance of their applications, even though the traffic passes through an external device.
Quick comparison: normal ARP exchange vs ARP poisoning
| Element | Normal ARP exchange | ARP poisoning |
|---|---|---|
| Who initiates | A host needing the MAC for a given IP | The attacker initiates and sends forged replies |
| Verification of the response | No cryptographic verification | Also none — hence the effectiveness of the attack |
| Persistence of the entry | Temporary, refreshed by normal requests | Maintained by repeated forged replies |
| Possibility of manual detection | Possible, requires checking ARP tables | Difficult without monitoring — symptoms may be subtle |
When ARP poisoning is particularly dangerous
The attack becomes critical when the network contains resources sending data in unencrypted form or when:
the network is flat, without segmentation;
user devices do not use VPN or HTTPS as a mandatory standard;
there are no layer-2 control mechanisms (DAI, Port Security) and no systems for network traffic analysis.
In such conditions, ARP spoofing can be not only a reconnaissance phase but the beginning of more serious attacks: privilege escalation, identity theft, malware installation.
What are the consequences of a successful attack?
A successful ARP spoofing attack is always accompanied by one of two phenomena: eavesdropping and traffic manipulation (Man-in-the-Middle) or complete degradation of communication (DoS). In both cases, the consequences are serious because the attacker gains real control over the flow of data in the local network — and therefore over the most valuable asset of any organization: information in transit. For security teams, it is crucial to understand not only the symptoms, but also the full exploitation path: what exactly the attacker can do after successfully poisoning ARP tables, what the consequences are in higher layers and how this is reflected in telemetry data.
Eavesdropping and data theft (Sniffing)
This is the first and most common goal of a Man-in-the-Middle attack in a LAN. Once ARP tables are poisoned, the attacker’s device becomes the intermediary in communication between the victim and the gateway. Every packet passes through their interface before reaching the destination.
In practice, this means full visibility of:
HTTP requests and responses transmitted in plain text,
SMTP, POP3, FTP, Telnet, LDAP logins without TLS,
session cookies and authentication tokens,
usernames, account numbers, personal data and document metadata.
Using tools such as Wireshark, tcpdump or dsniff, the attacker can filter traffic and automatically extract credentials from application-layer protocols. As a result, they gain a complete picture of the user’s activity, including visited websites, file names or the content of HTTP requests.
From a SOC team’s perspective, detecting eavesdropping requires monitoring:
an unnatural number of ARP sessions compared to the baseline,
the appearance of a new host acting as a proxy in TCP flows,
simultaneous connections to the gateway and clients (a bidirectional MITM tunnel).
Session hijacking
When applications use cookies or tokens to maintain sessions and traffic is not fully encrypted, the attacker can intercept the session identifier and recreate the session on their own device.
This way, they log into the system “as” the user without needing to know the password.
Most common targets:
CMS and ERP administration panels,
web applications without enforced HTTPS,
webmail, banking and CRM interfaces.
Session hijacking is particularly dangerous when the application:
does not bind the session to the IP address or browser fingerprint,
does not use the Secure and HttpOnly attributes for cookies,
uses long-lived JWT tokens without rotation.
From a network perspective, at the moment of session takeover, the network traffic analysis system may record:
parallel TCP flows with the same session ID from different MAC addresses,
a change of source IP in the middle of the session,
inconsistent User-Agent or TLS fingerprint.
These are classic signals of a lateral session hijack resulting from a Man-in-the-Middle attack.
Traffic tampering (modification in transit)
In more advanced scenarios, the attacker not only listens but modifies traffic content in real time.
This can include:
replacing links to executable files,
injecting JavaScript into HTTP pages,
redirecting a user to a phishing site,
manipulating DNS or HTTP headers (e.g., Host, Location, Set-Cookie).
From the network layer perspective, the attack consists of intercepting the IP packet, reconstructing the payload and modifying it before passing it on. The attacker keeps checksums and TCP identifiers correct, so from the victim’s perspective the transmission appears completely valid.
NDR systems can detect such activity through:
analysis of changes in packet size (payload delta vs baseline),
differences in IP/TCP checksums despite no retransmission,
correlation of HTTP content (hash values) between the original and forwarded packet.
Such analysis requires full packet inspection (Deep Packet Inspection) or real-time payload integrity monitoring.
Layer-2 Denial-of-Service attacks
Not every ARP spoofing attack aims to intercept traffic. In some cases, the attacker intentionally breaks communication. All they need to do is send a forged ARP reply to the victim, mapping the gateway’s IP to a non-existent or random MAC address. The result: every attempt to send a packet fails, because frames cannot be delivered.
This type of DoS:
does not require high traffic volume,
is not visible on the firewall,
affects only selected hosts (e.g. employees of a specific department).
In network traffic analysis systems, ARP-based DoS appears as:
a sudden drop in outgoing flows from a host,
increased number of failed TCP retransmissions,
prolonged ARP requests without any response.
Lateral movement and privilege escalation
A successful Man-in-the-Middle attack is rarely the end of the attacker’s actions. After capturing credentials or session tokens, the attacker uses them to:
move across other LAN segments (lateral movement),
gain access to management systems (AD, DNS, DHCP),
inject malware or backdoors into the infrastructure.
At this stage, detecting the attack requires integrating network traffic analysis with SIEM and EDR to correlate network behavior (unusual connections) with host activity (new processes, logins, file exports).
Packet flow analysis — how an NDR system sees a Man-in-the-Middle attack
NDR systems can analyze data in real time, combining L2, L3 and L4 traffic into a unified view. Below is an example snippet of a recorded attack in the packet view:
Analytical interpretation:
Lines 121–122: a classic ARP poisoning pattern — the same MAC (aa:bb:cc:dd:ee:ff) assigned to two IP addresses (gateway and host).
Lines 123–124: HTTP traffic from the victim and the gateway appears at the same time — the attacker intercepts both sides of the session.
Lines 125–126: the local connection between the host and the gateway is now terminated by the attacker, who acts as a proxy.
Additionally, the NDR correlates this activity with TCP metadata:
a 72% increase in RTT compared to the baseline,
asymmetry in packet counts (sent/received),
appearance of a new hop in the path (traceroute delta = +1).
This is sufficient to confirm an active Man-in-the-Middle attack and trigger response — for example, automatic port isolation or forwarding the event to the SIEM.
Business and regulatory impact
The consequences of successful ARP spoofing go beyond technical aspects. From an organizational perspective, this includes:
breach of confidentiality of personal data — under GDPR this requires incident notification,
loss of data integrity — risk of errors in transactions, reports or data transfers,
disruption of business continuity — outages in communication or critical services,
reputational damage — eavesdropping or tampering with internal traffic often reaches the media faster than internal communication.
Therefore, ARP spoofing should be treated in security policies on the same level as application-layer attacks and DDoS incidents (link to our DDoS article).
Table of technical and operational consequences
| Incident category | Attack mechanism | Technical symptoms | Potential business impact | Response priority |
|---|---|---|---|---|
| Eavesdropping (Sniffing) | Interception of ARP/MAC-based traffic | Unusual TCP flows, new intermediary in communication | Loss of data confidentiality, credential theft | Critical |
| Session hijacking | Capture of tokens or cookies | Parallel sessions from different IP/MAC | Unauthorized system access, fraud | Critical |
| Traffic modification | Payload manipulation | Checksum changes, HTTP hash anomalies | Code injection, phishing | Critical |
| L2 DoS | Mapping IP → forged MAC | No communication, repeated ARP requests | Operational downtime, loss of availability | High |
| Lateral movement | Use of captured data | New connections in segments | Incident spread | High |
The consequences of successful ARP spoofing are multi-layered — from simple sniffing to full infrastructure compromise. The greatest danger is not the moment of poisoning itself, but the long-term effects: loss of confidentiality, session takeover, loss of data integrity and service disruption. Thanks to NDR-class systems, an organization can see the attack in full context — not just as an ARP conflict, but as a chain of logically related events across layers 2–4. This enables precise response before the compromise occurs and turns the incident into a source of insight into the actual security posture of the LAN.
How a Man-in-the-Middle attack appears in network data — symptoms, correlations and detection logic
Recognising ARP spoofing in practice requires more than just noticing an unusual entry in an ARP table. For experienced SOC teams or NOC administrators, what matters is the correlation of events at layers 2, 3 and 4, observed in the context of the entire network topology and typical communication patterns. Only then can one confirm with high probability that this is a real Man-in-the-Middle attack, and not a configuration error or an address collision.
NDR (Network Detection and Response) systems — such as Sycope — analyse not only individual ARP packets, but also their temporal distribution, direction, repetition and impact on other protocols (TCP, DNS, HTTP). Thanks to this, they can distinguish genuine topology changes from active ARP table poisoning.
Duplicate MAC addresses — the clearest layer-2 anomaly signal
In a LAN environment, each MAC address should be unique within a given segment. When the detection system records that the same MAC address has been assigned to two or more IP addresses, a classic ARP poisoning pattern emerges.
From a technical point of view, it looks like this: host A (the victim) and the network gateway receive forged ARP replies from the attacker, which overwrite entries in their tables. As a result, traffic between them starts to pass through an intermediate device.
Traffic analysis systems (e.g. Sycope) monitor such phenomena not only at a single point, but also over time — they create temporal correlations between events. If the same MAC is reported with different IP addresses in a short interval (e.g. 10–30 seconds), the alert is assigned a high risk weight.
Example scenario:
In well-managed networks, such an alert is a clear indication that a Man-in-the-Middle attack has begun.
Volumetric and semantic patterns — anomalies in ARP communication
The second type of symptoms concerns the volume and nature of ARP communication.
In a healthy network, ARP traffic is moderate and closely dependent on the number of hosts and cache refresh intervals. In the case of ARP spoofing, a sudden, unnatural increase in the number of ARP packets appears — especially replies (ARP Reply) that do not correspond to any requests (ARP Request).
Traffic analysis systems detect this pattern by:
monitoring the Request/Reply ratio over time;
analysing the number of gratuitous ARP packets;
identifying hosts that generate excessive replies without prior requests.
Expert interpretation:
The attacker maintains ARP table “poisoning” by sending gratuitous replies every few seconds to overwrite correct entries. Monitoring systems combine this increase with NetFlow data — if the same host generates a large volume of ARP and simultaneously participates in TCP flows that were not previously observed, the risk of a confirmed attack grows exponentially.
Correlation with switch logs — MAC flapping and topology anomaly
ARP poisoning is not only visible in packets. Traces also appear in the network infrastructure: switches record so-called MAC flapping — the rapid movement of the same MAC address between different ports.
This is a particularly valuable indicator because it links the logical layer (ARP) with the physical one (ports). Syslog or SNMP logs may include entries such as:
%SW_MGMT-4-MAC_FLAP: MAC aa:bb:cc:dd:ee:ff moved from Gi1/0/5 to Gi1/0/23
Such a change is unnatural if it does not result from moving a host or reconfiguring the network. An NDR system that collects data from multiple sources can combine this information into a contextual event picture: a host with a given MAC appears on several ports, generates unusual ARP traffic and participates in TCP flows with hosts it did not communicate with before.
This is an example of multi-source correlation — not a single alert, but a convergence of symptoms that increases detection reliability.
Layer-3 and layer-4 effects — degradation of transmission quality
At the moment when traffic starts to pass through an intermediary, the characteristics of TCP and UDP connections change. This is visible in telemetry data:
an increase in RTT (Round Trip Time) between the host and the gateway,
irregular jitter and TCP retransmissions,
reduced throughput and anomalies in flow shape (e.g. a sudden drop in MSS or TCP window size).
In a network traffic analysis system, this can be observed as:
a change in the latency profile for a specific VLAN segment,
asymmetric TCP flows (request and response following different paths),
an increase in the number of incomplete TCP sessions (SYN without ACK).
Such symptoms are not evidence in themselves, but when combined with duplicate MACs and increased ARP traffic, they indicate an active Man-in-the-Middle attack.
Multi-layer anomaly correlation — how detection works in practice
Advanced detection is not based on a single indicator, but on a weighted model combining multiple phenomena. Systems such as Sycope can use rule-based logic or behavioural learning, where each deviation increases the risk level:
| Indicator | Description | Detection weight |
|---|---|---|
| MAC duplicate | The same MAC associated with multiple IPs | 0.9 |
| Gratuitous ARP | Increase in replies without requests | 0.7 |
| MAC flapping | Change of physical port for the same MAC | 0.6 |
| TCP asymmetry | Traffic passing through a new intermediary node | 0.5 |
| Increased RTT / retransmissions | Flow anomaly | 0.4 |
Combining three or more symptoms above a threshold (e.g. 2.0) results in an automatic alert classified as “ARP-based MITM”.
Case study — how a Man-in-the-Middle attack looks in real data
In an ARP packet captured by the system, the following repeated entries can be observed:
Frame 124: ARP, Reply 192.168.1.1 is-at aa:bb:cc:dd:ee:ff
Frame 125: ARP, Reply 192.168.1.137 is-at aa:bb:cc:dd:ee:ff
Temporal analysis shows that these packets appear at 5-second intervals throughout the session. At the same time, NetFlow metadata shows a new host (MAC: aa:bb:cc:dd:ee:ff) participating in HTTP flows between 192.168.1.137 and the external server 93.184.216.34 (example.com).
This is a classic example of a confirmed Man-in-the-Middle attack using ARP spoofing: traffic still reaches its destination, but every packet passes through an additional intermediary point. The system can immediately generate a high-risk alert and recommend automatic port isolation on the switch.
Expert interpretation: what distinguishes reactive from proactive analysis
Manual attack detection (e.g. using arp -a or comparing ARP tables) is a reactive method — it allows you to identify the problem only when it is already in progress.
NDR-class systems that use real-time network traffic analysis enable proactive detection of anomalies at the moment when the poisoning process is just beginning.
The difference can be reduced to three dimensions:
| Criterion | Manual analysis | Real-time analysis |
|---|---|---|
| Scope | Selected hosts | Entire network (100% of traffic) |
| Reaction time | After the fact | During the attack |
| Data source | ARP tables | Packets, flows, logs, telemetry |
| Correlation | None | Automatic, multi-layer |
| Result | Diagnosis | Detection + response (alert, isolation) |
ARP spoofing leaves clear traces in network data, but they are visible only when the system looks beyond a single packet. The most reliable indicators are:
MAC duplicates assigned to different IPs,
an increase in the number of gratuitous ARP packets,
MAC flapping on switches,
anomalies in TCP flows and increased latency.
Combining these symptoms within contextual analysis makes it possible to precisely detect a Man-in-the-Middle attack in real time. In the next part of the article, we will show how to use network traffic analysis to automatically recognise such patterns and respond immediately — before the attacker manages to capture anything.
Step by step: how to use network traffic analysis to detect anomalies
Why manual analysis is not enough
The arp -a command or viewing the cache are useful only post factum. They give you a snapshot of a single host’s state, do not show the dynamics of changes and do not cover the entire broadcast domain. In practice, they:
are reactive rather than proactive
do not scale to hundreds of VLANs and thousands of hosts
do not build a baseline and do not detect deviations over time
The conclusion is simple: you need a system that observes everything, understands what is normal, detects deviations and automatically correlates signals.
The role of NDR-class network traffic analysis systems
A system like Sycope acts as a non-invasive observational layer. The main assumptions are:
Coverage: visibility of traffic in critical segments at L3–L4
Real time: processing packet streams and metadata without operational delays
Baseline: a model of normal behaviour for ARP and application traffic across host, VLAN, switch port, service
Correlation: combining L2 ARP signals with L3 and L4 and switch telemetry
Data sources worth including:
packet traffic and flow metadata
switch and controller logs and telemetry
DHCP and RADIUS for mapping IP to identity
DNS and application session attributes for context
Detection pipeline — from signal to decision
Ingest and normalisation
ARP packets and L3 traffic are decoded into a common model. Key attributes are extracted: sender IP, sender MAC, target IP, opcode, time interval.
Baseline learning
The system determines the natural ARP intensity per segment and typical IP-to-MAC pairs. It also creates a map of topology and MAC-to-switch-port assignments.
L2 signal rules
Lightweight rules are triggered, such as: MAC duplicate, gratuitous ARP without prior request, high share of ARP Reply, MAC flapping on a port.
Multi-layer correlation
L2 signals are combined with L3 and L4 anomalies: TCP asymmetry, increased RTT, incomplete sessions, unknown flows to a new intermediary.
Risk assessment and de-duplication
Each case is assigned a weight and confidence level. Events are merged into a single incident with a timeline and evidence trail.
Alert and reaction workflow
The alert includes context: suspicious MAC, related IPs, ports, VLAN, indicators and a PCAP sample or event reconstruction.
How the system detects the attack — rules and thresholds that work
Below are example rules implemented in the detection engine. The notation is pseudocode so it can easily be mapped to any system.
R1. MAC duplicate in a short window
IF count_distinct(IP) mapped_to(MAC=X) within 30s >= 2
THEN raise indicator “Duplicate MAC” severity=high
R2. Gratuitous ARP unnaturally frequent
IF ARP.reply_without_request_ratio(segment) > baseline(segment) * 5
AND count(ARP.reply from Host H) within 60s > 30
THEN indicator “Gratuitous ARP surge” severity=medium
R3. MAC flapping on the switch
IF MAC X observed_on_ports >= 2 within 60s
THEN indicator “MAC flapping” severity=medium context=ports
R4. TCP asymmetry and degradation
IF RTT(host A -> gateway) increases by > 50% vs 24h baseline
AND retransmissions(A) > baseline(A) * 3
THEN indicator “Transport degradation” severity=medium
MITM-ARP correlation rule
IF R1 AND (R2 OR R3) AND (R4 OR NewFlow(A->UnknownPeer))
THEN ALERT “ARP-based Man-in-the-Middle” severity=critical
Visualising the attack — what NOC and SOC should see
A good dashboard does not just display an alert label. It should assemble the incident into a complete picture so that an analyst can make a decision in a few seconds.
Example alert message in the event view:
ARP conflict detected
MAC address [aa:bb:cc:dd:ee:ff] used by IP [192.168.1.1 — GATEWAY]
and IP [192.168.1.137 — ATTACKER]
Segment: VLAN 20 | Switch: sw-core-01 | Ports: Gi1/0/5, Gi1/0/23
Time: 2025-10-24 12:01:05–12:03:42 | Status: Active
Indicators: Duplicate MAC, Gratuitous ARP surge, MAC flapping, RTT↑ +72%
Artifacts: PCAP 12 MB, NetFlow 38 records, syslog 4 entries
Recommendations: Disconnect port Gi1/0/23, clear ARP on the gateway, invalidate sessions
The panel should provide:
a graph of ARP intensity over time with marked threshold and baseline
an IP-to-MAC map with lines indicating the conflict
topology context: VLAN, switch, port
a button to generate a PCAP dump and a reaction playbook
Operational table — signal, source, logic, threshold, confidence
| Signal | Source | Detection logic | Example threshold | Confidence |
|---|---|---|---|---|
| MAC duplicate | ARP packets | Same MAC assigned to ≥ 2 IPs in 30 s | 2 IPs in 30 s | Very high |
| Gratuitous ARP surge | ARP packets | Replies without requests exceed baseline | 5× baseline | High |
| MAC flapping | Syslog, SNMP, telemetry | MAC visible on multiple ports in a short window | 2 ports in 60 s | Medium–high |
| TCP asymmetry and degradation | Flow, transport metrics | RTT and retransmissions above baseline | RTT +50%, REXMIT ×3 | Medium |
| New intermediary in the path | Flow, tracer, topology | New node appears in the A↔gateway path | 1 new hop | High |
Why network monitoring is the only effective method in real time
An attack based on ARP spoofing exploits the fundamental trust of the protocol. You will not see it in application logs, you will not catch it with an edge filter and the endpoint will not always react. Only continuous network monitoring with full coverage and multi-layer correlation:
detects deviations immediately, before data theft occurs
provides evidential artefacts for forensics
enables automated reaction at the port and VLAN level
A practical measure of effectiveness is:
TTD (time to detect) below one minute
MTTR (mean time to restore) to clean connectivity and ARP tables below fifteen minutes
FPR (false positive rate) low thanks to signal correlation
From detection to response — SOC/NDR operational logic
Detecting an anomaly is only half the success. The value of an NDR-class system is revealed in an integrated response cycle: from identification to complete removal of the threat from the network. This is where the playbook comes into play – a predefined set of actions that SOC or NOC can perform immediately after confirming a Man-in-the-Middle attack.
The goal is not only to “put out the fire”, but to restore the original state of the network, collect evidence and secure the environment against incident recurrence. An NDR system such as Sycope can automatically pass context to SIEM/SOAR tools, which will trigger this process according to a defined scenario.
The playbook should combine three elements:
rapid isolation of the source to stop the attack in real time,
reconstruction of topology and cleaning ARP entries to restore correct communication,
preservation of traces and implementation of permanent measures that will prevent the attack from recurring.
Below is a minimal yet complete set of operational steps.
Minimal playbook in an NDR system
| Stage | Action | Operational goal | Tool / responsibility |
|---|---|---|---|
| 1. Detection | Detect the “ARP-based MITM” alert through network traffic analysis | Confirm the anomaly and identify the source | NDR system (Sycope) |
| 2. Verification | Correlate indicators (MAC duplicate, gratuitous ARP, TCP asymmetry) | Eliminate a false positive | SOC analyst |
| 3. Isolation | Disconnect the port or VLAN of the suspected host | Immediately stop the attack | NOC / Switch CLI / SOAR API |
| 4. State restoration | Clear ARP cache (arp -d *) on gateways and hosts | Restore correct mappings | Network administrator |
| 5. Evidence analysis | Export PCAP, NetFlow, ARP logs and syslog | Confirm mechanism and vector | SOC / Forensics |
| 6. Session invalidation | Force re-login and reset tokens | Block potentially hijacked sessions | Application security team |
| 7. Permanent remediation | Enable DAI, port security, ARP thresholds | Protect against recurrence | Network architect |
| 8. Documentation and report | Log the incident, update detection rules | Train the system for the future | SOC lead / CISO |
In the ideal scenario, the system detects a Man-in-the-Middle attack in less than 60 seconds (TTD), and full restoration of the correct network state (MTTR) takes no more than fifteen minutes. The key is not only precise network traffic analysis, but also automation of operational decisions. Thanks to ready-made playbooks and integration with switch infrastructure, Sycope can act not as a passive observer, but as an active defence component — reacting before the user notices that anything is wrong.
Prevention and response: best practices for LAN security
Attacks such as ARP spoofing are difficult to eliminate completely because they exploit a trusted and fundamental layer-2 protocol.
For this reason, an effective protection strategy must include three complementary pillars:
Passive methods – protecting data even if traffic is intercepted.
Active methods – hindering or blocking the attack mechanism itself.
Proactive methods – ensuring detection and response in real time.
Only the synergy of these approaches builds LAN resilience, reducing the risk of both eavesdropping and communication sabotage.
Passive methods — protecting data from being read
The passive security layer does not stop the attack itself, but eliminates the consequences of compromised data confidentiality. In practice, this means that even if an attacker intercepts traffic, they will not be able to read anything.
Encryption above all
HTTPS / TLS 1.3 – full encryption of HTTP sessions minimises the risk of passwords, tokens and cookies leaking.
SSH / SFTP – all administrative communication in the network (CLI, file transfers) should be tunnelled through an encrypted channel.
VPN (IPsec / SSL) – provides confidentiality and integrity of traffic between LAN segments and remote users.
DNS over HTTPS / DNS over TLS – hides DNS queries, which are often the first target of a MITM attacker.
Expert practice:
Enforce encrypted protocols in application and network device configuration.
Use organisational certificates (CA) and HSTS to avoid downgrades.
Regularly test SSL/TLS configurations (e.g. with the testssl.sh tool) for vulnerabilities.
Active methods — blocking the attack vector
Here the goal is not to protect content, but to prevent the attacker from inserting themselves into the communication path.
Static ARP tables
This is the most direct way to secure the network: the administrator manually assigns fixed IP↔MAC mappings for critical hosts (servers, gateways, controllers).
As a result, entries cannot be overwritten by forged ARP replies.
Advantages:
Resistance to ARP poisoning within the defined IP/MAC pairs.
Certainty of mapping for key devices (gateway, DHCP, DNS, critical servers).
Limitations:
Lack of scalability – maintaining thousands of static entries is unrealistic in dynamic environments.
Lack of flexibility – changing a device requires manual configuration updates.
Potential administrative errors – a wrong entry = loss of connectivity.
In practice, static ARP tables work well in infrastructure segments and closed environments (e.g. OT, server rooms, SCADA systems).
Dynamic ARP inspection (DAI) and port security
Advanced enterprise-class network switches (Cisco, Juniper, Extreme, HP, etc.) offer native features that protect against ARP poisoning.
Dynamic ARP inspection (DAI)
This mechanism analyses every ARP request and reply on the fly, comparing them with trusted sources — for example, the DHCP snooping table.
If an IP↔MAC entry does not match what comes from the DHCP server, the packet is dropped.
Advantages:
Protects against spoofing even in large, dynamic networks.
Integrates with authentication mechanisms (802.1X).
Supports logging and alerting at switch level.
Port security
Limits the number of MAC addresses that can appear on a given port. If a new MAC is detected, the port can be automatically shut down or moved into a protected state (shutdown / restrict).
This is an effective way to block attempts to impersonate other devices in real time — especially in office networks and BYOD environments.
Proactive methods — detection and response
In practice, even the most restrictive configurations will not provide complete tightness. New devices, segments, misconfigurations or DHCP failures create gaps that can be exploited.
That is why continuous network monitoring and network traffic analysis become the ultimate security layer — the safety net that detects every attack as soon as it begins.
NDR-class systems (such as Sycope):
observe ARP traffic across the entire broadcast domain,
identify anomalies in real time (MAC duplicates, gratuitous ARP, flapping),
correlate data from transport and application layers,
visualise IP↔MAC conflicts with port- and device-level precision,
automate response — e.g. disconnecting a port or notifying SIEM/SOAR.
In dynamic cloud and virtual environments, this is the only way to effectively detect ARP poisoning attempts before sessions are hijacked or data is stolen.
After detecting an incident — SOC/NOC response flow
Regardless of the alert source (NDR system, switch, SIEM), the response should follow a standard playbook.
| Step | Action | Operational goal |
|---|---|---|
| 1 | Source identification – confirm the attacker’s MAC and IP address in the logs | Determine the vector and scope of the attack |
| 2 | Host isolation – disconnect the switch port or move the device to a quarantine VLAN | Stop the attack in real time |
| 3 | ARP table restoration – clear cache (arp -d *) on gateways and hosts | Restore correct routing |
| 4 | Session invalidation – force re-login, reset tokens | Eliminate the risk of account takeover |
| 5 | Forensic analysis – export PCAP, NetFlow, syslog, identify traces | Preserve evidence and source |
| 6 | Strengthening protection – enable DAI, port security, NDR rules | Prevent the incident from recurring |
In an environment covered by network monitoring, reaction time (MTTR) should be a few minutes, and TTD (Time To Detect) — below one minute.
Complementarity of prevention and detection
It is worth emphasising: there is no single mechanism that will provide complete LAN security.
Static ARP and DAI reduce the attack surface, but do not guarantee detection. NDR systems based on network traffic analysis do not block packets, but inform about every deviation from the norm.
Only the combination of:
encryption (passive data protection),
strict network policies (DAI, port security), and
continuous traffic monitoring (anomaly detection)
creates a complete resilience model.
Conclusions and best practices
ARP is not outdated — but still dangerously trusting
The ARP protocol is a pillar of communication in local networks, but its design does not include any verification of message authenticity. This makes it an ideal target for attackers: in an environment without control and correlation, even a single host can poison the ARP tables of dozens of devices within seconds.
That is why the key principle of modern LANs should be “trust based on evidence, not on protocols designed 40 years ago.”
Layer-2 detection is just as important as application-level monitoring
Many administrators focus on firewalls, SIEMs and EDR systems while ignoring layer 2 — where most internal attacks begin.
ARP spoofing leaves no traces in server or application logs — its presence can only be detected through continuous network traffic analysis.
Therefore, the strategic security principle should be: “You cannot secure what you cannot see.”
Early detection is cheaper than response
The cost of responding to a successful Man-in-the-Middle attack grows exponentially with every minute.
The sooner a system detects MAC duplicates or unusual gratuitous ARP, the smaller the impact on users and data. In practice, every minute of delay means:
risk of credential loss,
session hijacking,
degradation of critical services.
For this reason, real-time monitoring is not a luxury but a necessity — especially in environments with highly dynamic addressing (DHCP, IoT, BYOD).
Technical prevention only makes sense when combined with visibility
Static ARP tables, DAI and port security can effectively block individual vectors, but none of these mechanisms operate in a vacuum. Their value increases only when combined with behavioural context: who, when, where and for how long generates ARP traffic.
This is why the best security environments combine preventive mechanisms (network configuration) with continuous observation and learning of device behaviour.
“Zero Trust” starts in the LAN
The Zero Trust model is not only about applications and users — its implementation should begin at the very bottom of the network stack. Every device in the LAN should be verified, profiled and monitored.
In practice this means:
observing all ARP, DHCP, DNS and ICMP messages,
automatic detection of new MAC addresses and their history,
building trust relationships based on telemetry rather than default rules.
Automation of response is the next step in evolution
NDR-class systems not only display anomalies — they can act. Integration with SIEM and SOAR allows automatic disconnection of a host, clearing ARP tables, and even modifying switch configuration.
This is the direction in which network security is heading: from observation to autonomous response, reducing MTTR from hours to minutes.
Administrator and user education still matters
Even the best monitoring cannot replace awareness. Administrators should regularly analyse alerts related to ARP and understand their context, and users should know the symptoms of a potential MITM attack (certificate warnings, sudden VPN disconnects).
The best organisations combine technology with process: training, playbooks and automated response into one coherent defence ecosystem.
The value of monitoring goes beyond security
Network traffic analysis in the context of LAN security brings additional value:
improves infrastructure performance (early detection of collisions and anomalies),
enables optimisation of routing and VLAN segmentation,
supports compliance (GDPR, ISO 27001, NIS2).
In practice, it is an investment in the stability of the entire IT ecosystem, not only in security.
The biggest mistake is assuming “it won’t happen to us”
ARP spoofing is not a laboratory attack — it is a real, everyday problem in corporate, office and industrial networks. It occurs even in virtual and cloud environments where machines share logical interfaces.
Therefore, instead of asking if, we should ask when and how quickly we will detect it.
Key takeaway: visibility is the new security boundary
Attacks evolve, but the underlying network mechanisms remain the same. The answer is not to replace protocols, but to observe and analyse them intelligently.
Organisations that invest in continuous network monitoring and systems such as Sycope gain not only resilience against Man-in-the-Middle attacks but also full awareness of what is really happening in their network.
Because security today is not about building walls — it is about seeing every move before someone else does.
FAQ
ARP spoofing is a type of Man-in-the-Middle attack where an attacker sends forged ARP packets to disrupt the normal IP-to-MAC mapping in a network, allowing them to intercept, modify, or block traffic. It's dangerous because it exploits trust within the network, making it difficult to detect without proactive monitoring.
ARP poisoning involves sending forged ARP replies to target hosts, misleading them into believing that the attacker's MAC address is associated with a legitimate IP address, such as a gateway. This enables the attacker to intercept communications between the target hosts and access or manipulate data.
Common symptoms include duplicate MAC addresses assigned to multiple IPs, increased ARP traffic volume, loss of connectivity or network response, and unusual transmission delays. Detecting these symptoms often requires network traffic analysis and monitoring of anomalies in ARP communication.
Prevention methods include encrypting transmissions using HTTPS, SSH, or VPN, implementing advanced switch features like Dynamic ARP Inspection (DAI) and Port Security, and continuously monitoring network traffic to detect irregularities in real-time.
If ARP spoofing is detected, the response should include identifying the attacker’s MAC and IP addresses, isolating the suspected host, restoring correct ARP table entries, invalidating sessions to prevent account takeovers, conducting forensic analysis, and implementing enhanced security measures like enabling DAI or revising network policies.
