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GHSA-fc26-m9pf-v56q
Authentication Bypass in praisonai (GHSA-fc26-m9pf-v56q)
Summary
authentication bypass in praisonai (GHSA-fc26-m9pf-v56q). Risk of unauthorized operations or information disclosure. Exploitable via ``LINEAR_WEBHOOK_SECRET``. Mitigation: upgrade to `4.6.59` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **GHSA-fc26-m9pf-v56q** has been found in praisonai.
Attackers can target a specific entry point like ``LINEAR_WEBHOOK_SECRET`` over the network to misuse the product.
Risk of unauthorized operations or information disclosure. CVSS score: ?/10.
What to do: upgrade praisonai to **4.6.59** or later.
If unsure, ask your IT team or search "praisonai GHSA-fc26-m9pf-v56q" on the vendor's site.
GHSA-fc26-m9pf-v56q (praisonai) — CWE-287 /
Attack surface: `LINEAR_WEBHOOK_SECRET` / `praisonai` / `main` / `webhookTimestamp`
Patched: `4.6.59` — 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
**authentication bypass** (CWE-287) exists in praisonai. Attackers reach the vulnerable code path via ``LINEAR_WEBHOOK_SECRET`` without authentication.
📍 Affected scope
praisonai — . Attack surface: `LINEAR_WEBHOOK_SECRET` / `praisonai` / `main` / `webhookTimestamp`.
🔥 Severity
Severity: ?. Risk of unauthorized operations or information disclosure
🔧 How to fix
Update to **4.6.59**.
🛡️ 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 request patterns matching this CVE's known IOCs. Run `grep -r 'praisonai' .` 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 'praisonai' . | 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 `praisonai` 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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6Apply patch patch
Upgrade praisonai to 4.6.59ステージング環境で 4.6.59 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
Confirm patched version is live in production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
praisonai
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"4.6.59"}]}]