P2p Dos And Eclipse

Injectable Skill: P2P DoS and Eclipse Attacks

L1 trigger: L1_PATTERN=true AND (p2p/ OR network/ OR discovery/ OR libp2p OR devp2p OR enr OR discv5 detected in recon subsystem map) Inject Into: depth-network-surface Language: Go and Rust Finding prefix: [P2P-N] Status: v0.1 draft, Round 4 exemplars pending

Orchestrator Decomposition Guide

• Sections 1, 2: depth-network-surface (attack surface + DoS)
• Section 3: depth-state-trace (peer table state)
• Section 4: depth-edge-case (boundary/adversarial peer states)

When This Skill Activates

Recon identifies a P2P subsystem. Most attacks in this class are out-of-scope for typical bounty programs but are in scope for Plamen audits — firms like Sigma Prime and OpenZeppelin explicitly cover them. Severity downgrades to Low/Info when the exploit only eclipses a single node (see severity-matrix.md); upgrades when reachable by arbitrary peers and amplifies across the network.

1. Attack Surface Enumeration (Entry Points)

Every P2P subsystem has a finite set of entry points for remote adversary bytes. Enumerate them using LSP workspace/symbol and ast-grep:

Write the enumeration into scratchpad/p2p_surface.md before proceeding.

2. DoS Classes to Check per Entry Point

2a. Asymmetric processing cost

Attacker sends N bytes, node does O(N²) or O(N*log(N)) work. Classic example: decompression bombs, hash-map insertion of attacker-chosen keys (hash DoS), large RLP lists.

Check:

• For each decoder, is there a max size limit before parsing begins?
• For each list/vector field, is there a max element count enforced?
• For each recursive decoder, is there a max recursion depth?
• For each hash-map insert of attacker-controlled data, is the map key pre-hashed or is a SipHash-random-keyed map used?

Tag: [P2P-ASYMMETRIC:{loc}:{input-size}→{work-cost}]

2b. Unbounded memory growth

Handlers that buffer or queue indefinitely.

Check:

• Every channel/queue: does it have a bounded capacity? What happens on overflow — block, drop, or OOM?
• Every append / Vec::push in a loop that can be driven by adversary: is there a bound?
• Every peer-keyed map (peer → state): is there an eviction policy when size > threshold?

Tag: [P2P-UNBOUNDED:{structure}:{growth-driver}]

2c. Unbounded CPU: infinite loops or pathological inputs

Handlers that can loop forever or spend minutes on malicious input.

Check:

• Every for loop in a handler: what bounds termination? Attacker-controlled?
• Regex with catastrophic backtracking (if any regex is used on peer input)
• Crypto operations on unvalidated length inputs

Tag: [P2P-CPU:{loc}:{termination-condition}]

2d. Connection slot exhaustion

Attacker opens N connections with M peers, filling the connection table.

Check:

• What is the max inbound connection limit? (Geth: 50, Bitcoin: 125)
• Is there a per-IP limit? Per-/24-subnet limit? Per-ASN limit?
• How long can a half-open (TCP SYN + no handshake) connection hold a slot?
• Does the node prioritize connections from diverse IP ranges?
• Outbound bootstrap handshake cap: when a joining node receives a peer list from a bootnode, does it cap the number of addresses it attempts to handshake in parallel? Without a cap, a malicious bootnode (or a peer-list response with N>>peer-table-size) forces the joiner to exhaust file descriptors / memory / connection slots during startup. Verify both the per-bootstrap response cap AND the in-flight handshake concurrency limit.

Tag: [P2P-SLOTS:{limit}:{diversification}], [P2P-BOOTSTRAP-FLOOD:{cap-or-unbounded}]

2e. Amplification

Attacker sends small message, node sends large response — used to DDoS third parties.

Check:

• For every request-response pair, compare input size vs output size
• Discovery protocols (UDP) are especially dangerous — no handshake, easy spoofing
• Is source-address validation (rate-limited ENR responses, etc.) in place?

Tag: [P2P-AMPLIFY:{request-bytes}→{response-bytes}]

2g. Re-gossip dedup discipline (echo-chamber amplification)

For each gossip handler that RECEIVES data and then FORWARDS it to other peers (re-gossip), trace the dedup path. This is a separate concern from 2a (single-message cost) — it covers network-multiplication attacks.

Check:

• Is there a "recent-seen" or "recent-valid" cache that BLOCKS re-broadcast on duplicates?
• Is the cache check BEFORE the broadcast spawn / .send() call, not after?
• Is the cache key the message hash (not the message contents, which an attacker can mutate while preserving semantics)?
• Is the cache populated AFTER signature/validity verification, not before? Recording-as-seen pre-verification creates a "seen-cache poisoning" primitive: an attacker injects an invalid item with a valid ID, the cache records it, the legitimate version from honest peers is then dropped as "already seen".
• For each handler, walk the order of operations: verify_signature → record_seen → broadcast. Any other order is a finding.

Fail mode: an N-peer network re-gossips each message O(N²) times, saturating bandwidth in an "echo chamber" pattern. NEAR / Tendermint / Geth have all had variants of this bug. Combined with seen-cache poisoning, an attacker can both flood the network AND censor legitimate items.

Tag: [P2P-AMPLIFY:re-gossip-dedup:{file}:{line}] and [P2P-CACHE-POISON:record-before-verify:{file}:{line}]

2h. Sequential broadcast vs parallel broadcast

Many P2P implementations naively use for peer in active_peers { client.send(peer, msg).await; } to broadcast. Each peer's response time blocks the next. A single slow peer (intentional or not) delays the entire broadcast cycle.

Check:

• For each broadcast loop, identify whether peers are processed sequentially with .await or in parallel with tokio::join_all / FuturesUnordered / select!.
• For sequential broadcast loops, calculate worst-case wall-clock: peer_count × per-peer-timeout. If this exceeds block time, propagation is broken under adversarial peer growth.
• Cap the total broadcast peer count to a constant (e.g., 200 randomly sampled peers); rely on gossip amplification for full propagation.

Tag: [P2P-CPU:sequential-broadcast:{loc}]

3. Eclipse Attack Vectors

An eclipse attack isolates a target node by monopolizing its peer table entries.

3a. Peer table structure

• Identify the peer table data structure (Kademlia k-buckets, flat table, discovery v5 ENR table)
• For each bucket, what is the k value and eviction policy?
• Is peer selection stratified by IP/ASN diversity, or purely by XOR distance?

3b. Peer ID generation cost

• How expensive is it to produce a peer ID that lands in a target bucket?
• Ethereum discovery v5: node ID = hash(public key). Generating thousands of node IDs is cheap.
• Some protocols require proof-of-work for peer IDs; most don't.
• Is there a rate limit on accepting new peer announcements?

3c. Bootstrap / rejoin vulnerability

On restart, the node uses a static bootstrap list, then populates its peer table from responses. If an attacker can intercept or outrun the bootstrap response, they control the initial peer set.

Check: What bootnodes are used? Are they hardcoded or configurable? What happens if all bootnodes are unreachable?

3d. ENR/record poisoning

Discovery v5 uses signed ENRs. Can an attacker poison a victim's ENR cache with malicious entries?

Check: ENR signature verification on every incoming record. ENR seqnum monotonic update.

Tag: [ECLIPSE:{vector}:{countermeasure-state}]

Known exemplar class: devp2p issue #109 (Ethereum discv5 eclipse concerns); academic low-resource eclipse attacks on older Geth.

4. Peer Scoring and Banning

Most clients have a peer scoring system: peers that misbehave (send invalid data, stall, equivocate) accumulate negative score and get banned.

Patterns to flag

• Integer overflow in score: if score is i32, repeatedly adding -MAX causes wrap. Geth has historically had integer-overflow issues in peer scoring.
• Permanent ban on transient fault: banning on a single protocol error can be exploited to deny service to honest peers via spoofed errors
• Asymmetric scoring: does good behavior recover lost score? If not, a single bad day permanently bans a good peer
• Scoring based on attacker-controlled timing: if score updates on every packet and attacker can drive packet rate, scoring becomes attacker-controlled

Tag: [P2P-SCORE:{vulnerability-class}]

5. Gossip / Pubsub

If the protocol uses gossipsub or similar pubsub:

• Message deduplication: is there a seen-cache? How large? What TTL? Can it be exhausted?
• Topic validation: are topic names validated before subscribing? Can an attacker force the node to subscribe to an expensive topic?
• Mesh sizing: mesh degree (D, D_low, D_high) — are these enforced? Can an attacker manipulate mesh composition?
• Message size: max message size in the pubsub layer vs the application layer — mismatch is a DoS vector

Tag: [GOSSIP:{param}:{value-or-unbounded}]

6. Output schema

• Layer: network
• Bug class: asymmetric-cost / unbounded-resource / slot-exhaustion / amplification / eclipse / peer-score / gossip
• Preferred evidence tags: [FUZZ-PASS] (D2PFuzz or libfuzzer on decoder) > [LSP-TRACE] > [CODE-TRACE]
• Severity baseline: Medium by default; upgrade to High if network-wide amplification; downgrade to Low/Info if single-node eclipse only

7. Known bug exemplars (v0.2 — Round 4 verified)

1. NEAR Signature::verify pre-auth handshake panic (December 2023) — $150,000 bounty. In SECP256K1 branch of Signature::verify(), Message::from_slice(data).expect("32 bytes") panics when payload > 32 bytes; RecoveryId::from_i32().unwrap() panics on recovery byte > 3. A single crafted Tier1Handshake/Tier2Handshake message kills any node. Pre-auth = any peer can do it. Fixed PR #10385 (commit e0f0da5c3dde29122e956dfd905811890de9a570). Zellic Web3 Ping of Death. Skill catch point: pre-auth panic check — for every handshake / pre-auth message handler, trace every .unwrap(), .expect(), panic!(), slice index, conversion. Assert graceful error return for all input classes.

2. Marcus-Heilman low-resource Ethereum eclipse (2018) — Geth's Kademlia discovery table could be monopolized by an attacker with only 2 IPs. Fixed in geth 1.8 (Feb 2018). Low-Resource Eclipse Attacks on Ethereum. Skill catch point: Section 3a — bucket eviction policy, IP/ASN stratification, rate-limit on new peer announcements.

3. D2PFuzz differential p2p bugs across 5 clients (IEEE 2025) — network-layer differential fuzzer found 15 unique bugs, 12 previously unknown by mutating DevP2P messages and diffing responses across geth, erigon, reth, besu, nethermind. Network-Layer Differential Fuzzing for Ethereum. Skill catch point: Section 1 — enumerate every DevP2P message type; verify response semantics against spec for valid / malformed / boundary / timing inputs; compare against ≥2 other client responses.

4. Henningsen "false friends" Ethereum eclipse (2019) — follow-up to Marcus-Heilman. Geth's peer-eviction policy could be gamed with valid-looking false-friend nodes. Eclipsing Ethereum Peers with False Friends. Skill catch point: Section 4 — audit peer scoring for monotonicity; new peers from unknown sources must not displace established trusted peers.

5. Geth CVE-2025-24883 RLPx handshake crash — all-zero secp256k1 public key accepted without subgroup validation. Single malicious peer crashes any node. GHSA-q26p-9cq4-7fc2. Skill catch point: cryptographic handshake inputs must be validated as on-curve AND in-subgroup BEFORE any math operation. (Shared with bls-aggregation-audit Section 2.)

Critical methodology addition from Round 4 (pre-auth panic = single-packet node kill)

Insert as new Section 2f (highest priority): Pre-auth message handlers are the hottest P2P surface. Every panic in a pre-auth path is a single-packet node-kill primitive. Methodology:

• List every message handler reachable before authentication/handshake completion
• For each, ast-grep or manual-read: .unwrap(), .expect(, panic!(, slice indexing [i], type assertion .(T) without ok, unreachable!(), integer division
• Every one of these is a finding until proven bounded (e.g., a length check earlier in the call chain)

Tag: [P2P-PANIC-PREAUTH:{handler}:{panic-site}]

2i. Peer Scoring Symmetry Audit

Peer scoring only works if rewards AND penalties are both applied. A one-sided system lets malicious peers farm reputation without consequence. This section forces enumeration.

Required artifact: write {SCRATCHPAD}/peer_scoring_symmetry.md:

# Peer Scoring Symmetry: {protocol_name}

| Event | Reward path | Penalty path | Symmetric? |
|---|---|---|---|
| Successful block delivery | score.rs:L42 +1 | — | **ASYMMETRIC** |
| Invalid block response | — | score.rs:L78 -5 | OK |
| Health check failure | — | — | **MISSING** |
| /get_data served | +1 | — | **FARMABLE** |

Methodology:

1. Find the peer scoring module (peer_score, reputation, scoring).
2. Enumerate EVERY event type the scoring system knows about — extract from the enum/struct mapping events to score deltas, not from memory.
3. For each event, find BOTH reward and penalty paths. Missing either → ASYMMETRIC finding.
4. check_health specifically: does it decrement on HTTP errors / timeouts, or only on explicit Ok(false)? A no-op on failure is a finding.
5. Verify failure-class coverage: "only InvalidData triggers penalty" while "BlockPool" or other validation failures are silent → finding.
6. Data request endpoints (/get_data, request_blocks): if the success path increments score with no rate limit or deduplication → FARMABLE finding.
7. Asymmetric scoring is always at least Medium severity.

Tag: [PEER-SCORE-ASYMMETRIC:{event}], [PEER-SCORE-FARMABLE:{event}], [PEER-SCORE-NO-PENALTY:{failure_class}]

8. Fallback if primitives unavailable

• List files under p2p/ and discovery/
• Grep for handleRLP, decode_rlp, handle_message function definitions
• Check for explicit size limits: grep MaxSize, MAX_, limit
• Read the bootstrap node list

Cross-references

• Related: mempool-asymmetric-dos, consensus-safety-invariants (equivocation detection interacts with peer scoring)
• Consumed by: depth-network-surface
• Severity: docs/l1-mode/severity-matrix.md