How AI Detects TCP Reset Attacks on BGP Sessions

A lot of defenders assume that if a routing session is “internal” or “between trusted peers,” it’s effectively safe. Most companies get this wrong. The 2004 CISA alert on TCP injection and connection reset attacks is a reminder that foundational protocols can fail you in very practical ways—especially when you depend on persistent TCP connections like BGP does.

Here’s the uncomfortable part: the underlying weakness isn’t a weird edge case. It’s rooted in how TCP accepts packets that look plausible—particularly when an attacker can guess sequence numbers within the receive window. In BGP, where sessions stay up for long periods and window sizes can be large, that “plausible” bar can be low enough for attackers to knock sessions over repeatedly.

This post sits in our AI in Cybersecurity series for a reason. The lesson from 2004 is still current in 2025: protocol hardening matters, but detection speed matters more when adversaries can distribute attempts across botnets and blend into normal traffic. AI-driven network security is increasingly the difference between a brief hiccup and an operational incident.

Why TCP vulnerabilities still matter for mission networks

TCP injection isn’t “old news” because modern networks still rely on TCP for long-lived control-plane sessions, management channels, and critical application flows. If an attacker can terminate or desynchronize those sessions, the result is often denial of service, forced failovers, or cascading instability.

In the original advisory, the high-risk example is BGP, the Internet’s routing control plane. BGP commonly runs over TCP sessions that are:

• Persistent (long-lived)
• Often unauthenticated at the TCP layer unless explicitly protected
• Sensitive to disruption (sessions reset, reconverge, rebuild routes)

When those sessions flap repeatedly, you don’t just get “a disconnect.” You get routing churn, route dampening side effects, convergence delays, and sometimes collateral impact on unrelated services that share the same infrastructure.

The failure mode: “just one packet” can break a session

The core issue described by CISA is simple: if an attacker can inject a forged TCP packet with an acceptable sequence number, they can do damage. One of the most operationally painful versions is a forged TCP RST.

A spoofed RST that lands inside the acceptable receive window can cause one endpoint to drop the connection immediately—no application-layer negotiation required.

Why window size changes the attacker’s math

The advisory highlights a key operational detail defenders sometimes overlook: the TCP receive window defines the range of acceptable sequence numbers. A larger window means a larger “target” for guessed sequence numbers.

The source content includes concrete figures from analysis at the time:

• With 65,535-byte window sizes, an upstream of 80 Kbps could attempt enough packets to land an injected TCP packet roughly every ~5 minutes.
• With a T-1 (1.544 Mbps) connection, this could drop to ~15 seconds.

In 2025, an attacker doesn’t need a single fast line anyway. They can distribute attempts across many compromised hosts, which changes the operational picture from “hard” to “inevitable unless you harden and detect.”

What a TCP reset attack against BGP looks like in real life

A BGP reset attack is rarely cinematic. It’s annoying, persistent, and operationally expensive.

A typical pattern looks like this:

1. BGP session established between peers over TCP (port 179).
2. Attacker sends spoofed packets crafted to match the 4-tuple and land within the window.
3. A forged RST (or other disruptive segment) is accepted.
4. Session drops, BGP restarts the peering process.
5. Routes withdraw and re-advertise; traffic shifts; latency spikes; some flows break.
6. Repeat until the operator gives up, filters aggressively, or adds cryptographic protection.

Even if “routing recovers quickly after the attack ends” (as the advisory notes), sustained attacks create a chronic instability problem. For defense and national security environments, that’s more than a nuisance:

• ISR and mission applications depend on stable transport paths.
• Zero Trust overlays still require stable underlays.
• Outages and flaps complicate incident response when you need telemetry continuity.

People also ask: isn’t TLS enough?

TLS helps at the application layer, but it doesn’t stop a TCP-layer reset from tearing down the connection underneath it.

A clean way to say it:

TLS can stop data injection into an encrypted session, but it can’t prevent TCP from accepting a forged reset unless the transport or network layer is authenticated.

That’s why the original guidance emphasizes protections like TCP MD5 for BGP (RFC 2385) or tunneling BGP through IPsec.

The defensive baseline: hardening still pays off

AI is not a substitute for basic controls. It’s an amplifier. If your BGP or other persistent TCP sessions aren’t protected, you’re giving attackers too many easy options.

Control 1: Authenticate the session (not just the payload)

For BGP specifically, defenders have historically used:

• TCP MD5 signatures (RFC 2385) to authenticate TCP segments between peers
• IPsec to authenticate and protect traffic at the network layer

Practical stance: if you operate BGP for anything mission-relevant and you’re not using a modern equivalent of session authentication, you’re accepting avoidable risk.

Control 2: Filter spoofing at the edges (ingress and egress)

The advisory calls out ingress filtering and egress filtering as key mitigations. That’s not “nice to have.” Spoofing-enabled attacks live and die by poor filtering hygiene.

A policy-oriented checklist:

• Only allow expected sources to reach management/control-plane interfaces.
• Restrict inbound initiation to systems that actually provide public services.
• Treat unexpected outbound BGP-like traffic as a potential indicator of compromise.

Control 3: Isolate control-plane paths

Separating control and data channels reduces blast radius and noise. You can do this with:

• Separate VRFs / VLANs
• Dedicated VPNs
• Leased links or private transport
• Strong ACLs and route-policy boundaries

Isolation doesn’t “fix TCP,” but it reduces exposure and improves signal quality for detection.

Where AI-driven network security changes the outcome

Hardening reduces feasibility. AI detection reduces dwell time. When attackers distribute attempts, rate-limit themselves, and blend into background noise, signature-only approaches often lag.

AI-based threat detection is useful here because the observable behaviors are subtle but consistent:

• Micro-bursts of packets toward control-plane ports
• Odd sequence-number distributions (as inferred from endpoint responses and timing)
• Repeated session resets correlated across peers or regions
• Reconvergence and route churn patterns that don’t match maintenance windows

What to detect: signals that matter for TCP injection attempts

If you’re building detections (or evaluating vendors), look for models that can combine network telemetry + control-plane state + time-series correlation.

High-value signals include:

• BGP session flap frequency beyond baseline (per peer, per PoP)
• RST/ACK anomalies (rate, source diversity, TTL patterns, inconsistent paths)
• Asymmetric traffic observations (RST seen on one side but not the other, depending on vantage)
• Window-sized “probing cadence” behavior: repeated attempts spaced to cover a plausible sequence range
• Botnet-style distribution: low-rate attempts from many sources rather than high-rate from one

A snippet-worthy rule of thumb:

When a control-plane session drops, the question isn’t “did it recover?” It’s “did it drop for a reason you can prove?”

AI in SOC workflows: fewer pages, faster containment

In practice, the win isn’t “AI caught a spoofed RST.” The win is shortening the loop:

1. Detect abnormal reset patterns and correlate with routing instability.
2. Confirm likely spoofing by comparing path/TTL/ASN/geo consistency and endpoint logs.
3. Contain with automated ACL pushes, peer protection, temporary dampening strategies, or shifting to protected tunnels.
4. Hunt laterally for compromised internal systems generating suspicious egress.

If you’ve ever tried to investigate intermittent BGP flaps during peak operations, you know why this matters. Humans are good at deep analysis; they’re not good at watching 400 time series at once.

Autonomous defense for mission-critical infrastructure

For defense and national security environments, you often need response actions that are:

• Pre-approved (policy-based)
• Low-risk (minimal chance of self-inflicted outage)
• Auditable (why did the system block that traffic?)

AI helps when paired with constraints:

• Use AI to prioritize and recommend.
• Use policy engines to enforce safe actions (rate limit, ACL templates, isolate interfaces).
• Require human approval for disruptive changes (peer shutdowns, route-policy changes).

That hybrid approach is how you get speed without fragility.

A practical playbook: protect BGP and persistent TCP sessions now

If you want a defensible plan—one that stands up in an after-action review—use this sequence.

Step 1: Inventory “persistent TCP” dependencies

Don’t stop at BGP. Many environments have fragile long-lived sessions:

• Routing protocols and peering (BGP over TCP)
• OT/ICS gateways and historian links
• Remote management jump paths
• Replication streams (databases, message buses)

Document the endpoints, ports, expected peers, and baseline session durations.

Step 2: Add cryptographic protections where they actually stop resets

Pick controls that protect the transport or network layer, not just the app layer:

• BGP session authentication (where supported)
• IPsec between peers for high-value links
• Strict peer allowlists and control-plane policing

Step 3: Deploy AI-based anomaly detection tuned to routing reality

Generic anomaly models often drown in noise. Tune to your environment:

• Maintenance windows and planned flaps
• Known reconvergence patterns
• Peer-level baselines (some peers are naturally noisy)

Feed the model both network telemetry (flow, packet, firewall logs) and control-plane state (router events, BGP notifications).

Step 4: Automate the safest responses

Start with actions that reduce harm without risking new outages:

• Temporary rate limits on suspicious sources
• Automated ticketing with enriched evidence (peer, timeline, flows, inferred spoofing traits)
• Targeted ACLs for control-plane interfaces

Then mature toward closed-loop actions as confidence improves.

Why this 2004 alert still belongs in a 2025 AI in Cybersecurity series

The point of revisiting a TCP vulnerability advisory from 2004 isn’t nostalgia. It’s a reality check: some of the most damaging attack paths are “boring” protocol mechanics. Attackers love boring. It scales.

AI-driven cybersecurity earns its keep when it spots the patterns humans miss: low-rate distributed attempts, subtle timing signatures, and the early onset of routing instability before users start calling. Pair that detection with session authentication, filtering, and isolation, and you turn a brittle dependency into a resilient system.

If your team is responsible for mission networks, critical infrastructure, or defense-adjacent environments, take a hard look at your persistent TCP sessions—especially BGP. Which ones are authenticated? Which ones are merely assumed safe because “it’s just routing”? And if a peer started flapping every few minutes today, could you prove whether it was misconfiguration, link instability, or an injection-driven reset attack?