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CVE-2026-44716
high
CVSS 7.5
Path Traversal in pipecat-ai (CVE-2026-44716)
Summary
path traversal in pipecat-ai (CVE-2026-44716). Confidential information can be exposed externally. Exploitable via `GET /files/{filename`. Mitigation: upgrade to `1.2.0` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **CVE-2026-44716** has been found in pipecat-ai.
Attackers can target a specific entry point like `GET /files/{filename` over the network to misuse the product.
Confidential information can be exposed externally. CVSS score: 7.5/10.
What to do: upgrade pipecat-ai to **1.2.0** or later.
If unsure, ask your IT team or search "pipecat-ai CVE-2026-44716" on the vendor's site.
CVE-2026-44716 (pipecat-ai) — CWE-22 / CVSS v3 7.5
Attack vector: remote (network-reachable) / unauthenticated / no user interaction
Attack surface: GET /files/{filename / GET /files/.. / GET /files/recording.txt / GET /files/../../etc/passwd
Patched: `1.2.0` — 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
**Path traversal** (CWE-22) exists in pipecat-ai. Attackers reach the vulnerable code path via `GET /files/{filename` without authentication.
📍 Affected scope
pipecat-ai — . Attack surface: GET /files/{filename / GET /files/.. / GET /files/recording.txt / GET /files/../../etc/passwd.
🔥 Severity
Severity: High (CVSS 7.5/10). Confidential information can be exposed externally
🔧 How to fix
Update to **1.2.0**.
🛡️ 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 `GET /files/{filename` 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
-
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 'GET /files/{filename' /var/log/nginx/access.log | grep -E '(unusual_payload|sqli_pattern)'アクセスログで `GET /files/{filename` 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 1.2.0ステージング環境で 1.2.0 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 GET /files/{filename 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":"1.2.0"}]}]
PyPI
pipecat-ai
[{"type":"ECOSYSTEM","events":[{"introduced":"0.0.90"},{"fixed":"1.2.0"}]}]
References
- advisory https://nvd.nist.gov/vuln/detail/CVE-2026-44716
- exploit [email protected]
- package https://github.com/pipecat-ai/pipecat
- patch [email protected]
- patch [email protected]
- web [email protected]
- web https://github.com/advisories/GHSA-3363-2ph6-35wh