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HIGH severity

GHSA-4x6r-9v57-3gqw

HIGH

GHSA-4x6r-9v57-3gqw is a high-severity (CVSS 8.1) CWE-639 vulnerability in praisonai-platform. O3 Security confirms whether GHSA-4x6r-9v57-3gqw is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

praisonai-platform: IDOR in dependency endpoints allows cross-workspace issue linking, reading, and deletion due to missing ownership checks

Also known asCVE-2026-47406PYSEC-2026-2928
Published
May 29, 2026
Updated
Jul 13, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Aug 16, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for GHSA-4x6r-9v57-3gqw.

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs14th percentile — riskier than 14% of all scored CVEsHighest risk
0.00%0.24%0.49%0.73%0.2%0.2%Aug 26Aug 26

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-4x6r-9v57-3gqw plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 365,017 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍praisonai-platform

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Summary

Type: Insecure Direct Object Reference. The dependency endpoints (POST/GET /workspaces/{workspace_id}/issues/{issue_id}/dependencies and DELETE .../dependencies/{dep_id}) gate access on require_workspace_member(workspace_id) only, then dispatch to DependencyService calls that take URL/body-supplied issue and dependency IDs without verifying any of them belong to the membership-checked workspace. Most damaging: create_dependency accepts body.depends_on_issue_id from the request body — that ID is checked against nothing — letting an attacker create a "blocks" or "related" link between any two issues anywhere in the database. File: src/praisonai-platform/praisonai_platform/api/routes/dependencies.py, lines 22-58; services/dependency_service.py, lines 26-65. Root cause: the same Depends(require_workspace_member) default-min-role pattern as the companion IDORs, plus a service layer (DependencyService) where every method takes raw IDs and queries them directly. create(issue_id, depends_on_issue_id, ...) writes a row with no workspace verification on either ID. list_for_issue(issue_id) returns dependencies in either direction. delete(dep_id) is a primary-key delete with no workspace predicate.

Affected Code

File 1: src/praisonai-platform/praisonai_platform/api/routes/dependencies.py, lines 22-58.

@router.post("/", response_model=DependencyResponse, status_code=status.HTTP_201_CREATED)
async def create_dependency(
    workspace_id: str,
    issue_id: str,
    body: DependencyCreate,
    user: AuthIdentity = Depends(require_workspace_member),
    session: AsyncSession = Depends(get_db),
):
    svc = DependencyService(session)
    dep = await svc.create(issue_id, body.depends_on_issue_id, body.type)  # <-- BUG: neither id is workspace-checked
    return DependencyResponse.model_validate(dep)


@router.get("/", response_model=List[DependencyResponse])
async def list_dependencies(
    workspace_id: str,
    issue_id: str,
    user: AuthIdentity = Depends(require_workspace_member),
    session: AsyncSession = Depends(get_db),
):
    svc = DependencyService(session)
    deps = await svc.list_for_issue(issue_id)                              # <-- BUG: returns dependencies for any issue
    return [DependencyResponse.model_validate(d) for d in deps]


@router.delete("/{dep_id}", status_code=status.HTTP_204_NO_CONTENT)
async def delete_dependency(
    workspace_id: str,
    issue_id: str,
    dep_id: str,
    user: AuthIdentity = Depends(require_workspace_member),
    session: AsyncSession = Depends(get_db),
):
    svc = DependencyService(session)
    deleted = await svc.delete(dep_id)                                     # <-- BUG: deletes any dependency by id
    if not deleted:
        raise HTTPException(status_code=404, detail="Dependency not found")

File 2: src/praisonai-platform/praisonai_platform/services/dependency_service.py, lines 26-65.

async def create(self, issue_id: str, depends_on_issue_id: str, dep_type: str = "blocks") -> IssueDependency:
    if dep_type not in VALID_TYPES:
        raise ValueError(...)
    dep = IssueDependency(
        issue_id=issue_id,                                              # <-- accepts any
        depends_on_issue_id=depends_on_issue_id,                        # <-- accepts any (from request body)
        type=dep_type,
    )
    self._session.add(dep); await self._session.flush(); return dep

async def list_for_issue(self, issue_id: str) -> list[IssueDependency]:
    stmt = select(IssueDependency).where(
        (IssueDependency.issue_id == issue_id) | (IssueDependency.depends_on_issue_id == issue_id)
    )
    return list((await self._session.execute(stmt)).scalars().all())

async def delete(self, dep_id: str) -> bool:
    dep = await self.get(dep_id)                                        # session.get(IssueDependency, dep_id) — no workspace check
    ...

Why it's wrong: the request-body depends_on_issue_id is the worst part: an attacker can link any two issues across any two workspaces, polluting both workspaces' dependency graphs with attacker-chosen relationships ("blocks", "blocked_by", "related"). The triagers in the foreign workspace see their issue suddenly blocked by an unrelated foreign issue, breaking sprint planning and creating false correlation. The delete(dep_id) path lets an attacker remove legitimate cross-issue links between any two foreign workspaces, also disrupting their planning. The list_for_issue path leaks the dependency graph for any issue in the deployment.

Exploit Chain

  1. Attacker is a member of workspace W_attacker and harvests two foreign-workspace issue UUIDs I1 (in W_target1) and I2 (in W_target2). They leak via the activity feed, comment threads, error messages, exported dumps, the agent prompt history, or any other channel that ever serialises an issue ID. State: attacker holds two foreign issue UUIDs.
  2. Attacker sends POST /workspaces/W_attacker/issues/I1/dependencies with Authorization: Bearer <attacker_jwt> and body {"depends_on_issue_id": "I2", "type": "blocks"}. State: control flow enters create_dependency with issue_id=I1 (foreign), depends_on_issue_id=I2 (foreign).
  3. require_workspace_member(W_attacker, attacker) passes (attacker is a member of W_attacker). DependencyService.create(I1, I2, "blocks") writes a new row IssueDependency(issue_id=I1, depends_on_issue_id=I2, type="blocks"). State: there is now a cross-workspace dependency between two foreign issues, written by the attacker.
  4. The triage UIs of W_target1 and W_target2 now show that the foreign issue is blocked by an unrelated issue in another workspace. Workflow rules that key off "cannot close while blocked" will refuse to let the legitimate triagers close I1. State: foreign workflow disrupted.
  5. Attacker repeats with GET /workspaces/W_attacker/issues/I1/dependencies to read the dependency graph for any foreign issue (information disclosure, project relationship mapping), or with DELETE .../{dep_id} (after enumerating dep_ids via the list call) to strip legitimate dependencies between foreign issues, breaking blocked-by chains.
  6. Final state: with one workspace-member token, the attacker reads, writes, and deletes dependencies on every issue in the multi-tenant deployment, polluting the dependency graphs of foreign workspaces.

Security Impact

Severity: sec-high. CVSS 7.6: network attack, low complexity, low privileges, no user interaction, scope unchanged, high confidentiality (cross-workspace dependency graph disclosure), high integrity (cross-workspace dependency injection and deletion), no availability claim (workflow disruption is integrity, not availability). Attacker capability: read any issue's dependency graph; create arbitrary "blocks" / "blocked_by" / "related" links between any two issues across any two workspaces; delete any dependency by id. The most surprising primitive is the cross-workspace LINKING — the only one of the IDORs in this codebase where a single attacker request can affect TWO foreign workspaces at once. Preconditions: praisonai-platform is deployed multi-tenant; attacker has any membership token; foreign issue UUIDs are reachable. Differential: source-inspection-verified end-to-end. The asymmetry between this service (no workspace predicate anywhere) and MemberService.get(workspace_id, user_id) (correctly composite-keyed) confirms the gap. With the suggested fix below, the route would resolve both the URL issue_id and the body depends_on_issue_id against IssueService.get(workspace_id, ...) before allowing the dependency to be written.

Suggested Fix

Resolve every issue id (URL and body) against workspace_id at the route layer before dispatching. The route helper from the issue-IDOR companion advisory can be reused.

--- a/src/praisonai-platform/praisonai_platform/api/routes/dependencies.py
+++ b/src/praisonai-platform/praisonai_platform/api/routes/dependencies.py
@@ -22,11 +22,16 @@
 @router.post("/", response_model=DependencyResponse, status_code=status.HTTP_201_CREATED)
 async def create_dependency(
     workspace_id: str,
     issue_id: str,
     body: DependencyCreate,
     user: AuthIdentity = Depends(require_workspace_member),
     session: AsyncSession = Depends(get_db),
 ):
+    issue_svc = IssueService(session)
+    if await issue_svc.get(workspace_id, issue_id) is None:
+        raise HTTPException(status_code=404, detail="Issue not found")
+    if await issue_svc.get(workspace_id, body.depends_on_issue_id) is None:
+        raise HTTPException(status_code=404, detail="depends_on_issue_id not found in this workspace")
     svc = DependencyService(session)
     dep = await svc.create(issue_id, body.depends_on_issue_id, body.type)
     return DependencyResponse.model_validate(dep)

Apply the same issue_svc.get(workspace_id, issue_id) precondition to list_dependencies and delete_dependency (verifying both the issue and the dependency belong to workspace_id).

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIpraisonai-platformall versions0.1.4

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for praisonai-platform. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update praisonai-platform to 0.1.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-4x6r-9v57-3gqw is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether GHSA-4x6r-9v57-3gqw is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-4x6r-9v57-3gqw. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

## Summary **Type:** Insecure Direct Object Reference. The dependency endpoints (`POST/GET /workspaces/{workspace_id}/issues/{issue_id}/dependencies` and `DELETE .../dependencies/{dep_id}`) gate access on `require_workspace_member(workspace_id)` only, then dispatch to `DependencyService` calls that take URL/body-supplied issue and dependency IDs without verifying any of them belong to the membership-checked workspace. Most damaging: `create_dependency` accepts `body.depends_on_issue_id` from the request body — that ID is checked against nothing — letting an attacker create a "blocks" or "rela
O3 Security · Impact-Aware SCA

Is GHSA-4x6r-9v57-3gqw in your dependencies?

O3 detects GHSA-4x6r-9v57-3gqw across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-4x6r-9v57-3gqw: praisonai-platform… | O3 Security