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CVE-2026-54695
high
CVSS 7.5
Vulnerability in pipecat-ai (CVE-2026-54695)
Summary
vulnerability in pipecat-ai (CVE-2026-54695). Risk of unauthorized operations or information disclosure. Exploitable via `POST /start`. Mitigation: upgrade to `1.4.0` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **CVE-2026-54695** has been found in pipecat-ai.
Attackers can target a specific entry point like `POST /start` over the network to misuse the product.
Risk of unauthorized operations or information disclosure. CVSS score: 7.5/10.
What to do: upgrade pipecat-ai to **1.4.0** or later.
If unsure, ask your IT team or search "pipecat-ai CVE-2026-54695" on the vendor's site.
CVE-2026-54695 (pipecat-ai) — CWE-862 / CVSS v3 7.5
Attack vector: remote (network-reachable) / unauthenticated / no user interaction
Attack surface: POST /start / `callSid` / `call_id` / `TwilioFrameSerializer`
Patched: `1.4.0` — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
❓ What is the problem
**A vulnerability** (CWE-862) exists in pipecat-ai. Attackers reach the vulnerable code path via `POST /start` without authentication.
📍 Affected scope
pipecat-ai — . Attack surface: POST /start / `callSid` / `call_id` / `TwilioFrameSerializer`.
🔥 Severity
Severity: High (CVSS 7.5/10). Risk of unauthorized operations or information disclosure
🔧 How to fix
Update to **1.4.0**.
🛡️ Workaround
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
🔍 Detection
Search webserver/proxy logs for unusual `POST /start` requests with malformed payloads or SQL meta-characters. Run `grep -r 'pipecat-ai' .` against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response Actions (7 steps)
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
grep -r 'pipecat-ai' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で `pipecat-ai` を grep し、稼働しているサービス・バージョンを把握する。
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3Hunt for indicators of compromise detect
grep 'POST /start' /var/log/nginx/access.log | grep -E '(unusual_payload|sqli_pattern)'アクセスログで `POST /start` への異常なリクエスト (不正な認証ヘッダ・SQLメタ文字)を過去 30〜90日分捜索。WAF/SIEM があれば該当パスのアラート発火履歴を確認。
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6Apply patch patch
Upgrade pipecat-ai to 1.4.0ステージング環境で 1.4.0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスと、Step 3 で見つけた異常検知の続報チェックを含めること。
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7Post-deployment verification verify
Replay attack against POST /start on staging to confirm patch closes the vectorパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番では Step 3 と同じログクエリでアラート再発が無いか継続監視。
Affected packages
pip
pipecat-ai
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.4.0"}]}]