VAITP Dataset

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Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1611
1948
CVE-2026-45554
NiceGUI denial-of-service via log amplification in static asset routes.

NiceGUI is a Python-based UI framework. Prior to version 3.12.0, two FastAPI routes that serve per-component static assets in NiceGUI accept a sub-path parameter that may resolve to a directory rather than a file. Requests that resolve to a directory raise an unhandled RuntimeError inside Starlette's FileResponse, which Uvicorn writes to the server log as a full traceback. Because the routes are reachable without authentication, a remote attacker can amplify log volume and consume disk and log-pipeline capacity on any publicly reachable NiceGUI server. This issue has been patched in version 3.12.0.

Checking
Resource Management
Resource Exhaustion
Remote
1947
CVE-2026-45553
Local file inclusion vulnerability in NiceGUI's ui.restructured_text.

NiceGUI is a Python-based UI framework. Prior to version 3.12.0, ui.restructured_text() renders reStructuredText server-side with Docutils without disabling file insertion directives. When a NiceGUI application passes attacker-controlled content to ui.restructured_text(), an attacker can use standard Docutils directives (include, csv-table with :file:, raw with :file:) to read local files readable by the NiceGUI server process. Applications that only pass trusted static strings to ui.restructured_text() are not affected. This issue has been patched in version 3.12.0.

Checking
Input Validation and Sanitization
Local File Inclusion (LFI)
Remote
1946
CVE-2026-10300
SGLang `lora_path` manipulation in Inference Endpoint leads to an assertion.

A security vulnerability has been detected in SGLang 0.5.10.post1. Impacted is an unknown function of the file python/sglang/srt/lora/lora_manager.py of the component Inference HTTP Endpoint. Such manipulation of the argument lora_path leads to reachable assertion. The attack can be launched remotely. A high complexity level is associated with this attack. The exploitability is considered difficult. The exploit has been disclosed publicly and may be used. The pull request to fix this issue awaits acceptance.

Checking
Input Validation and Sanitization
Path Traversal
Remote
1945
CVE-2026-45426
Airflow log server auth bypass allows reading logs from other DAGs.

Exploitation requires the attacker to already be an authenticated Airflow worker holding a valid Log-server JWT issued for at least one Dag. Apache Airflow's Log server authorized JWT tokens against Dag IDs by applying Python's `str.lstrip()` to the requested path segment when verifying the JWT's `sub` claim. `str.lstrip()` strips any of a *set* of characters from the left (not a prefix), so a JWT issued for a Dag named e.g. `dag_a` would authorize log access to any other Dag whose name began with any subset of the characters `{d, a, g, _}` (e.g. `dag_attacker`, `aaaa_target`, `_dag_secret`). Such an authenticated worker could enumerate and read worker logs of other Dags whose names happened to share that character-class prefix, leaking task output and error traces beyond the documented per-Dag isolation boundary. Affects deployments relying on per-Dag log-access scoping (multi-team, shared-executor, shared-worker topologies). Users are advised to upgrade to `apache-airflow` 3.2.2 or later.

Checking
Authentication, Authorization, and Session Management
Poorly Designed Access Controls
Local
1944
CVE-2026-46561
pyLoad authenticated SSRF via redirect allows internal network access.

pyLoad is a free and open-source download manager written in Python. Prior to 0.5.0b3.dev100, the PREREQFUNCTION-based private IP check was not applied to HTTPRequest (used by the parse_urls API). An authenticated attacker can supply a URL pointing to an attacker-controlled server that responds with a 302 redirect to an internal/private IP address, bypassing the is_global_host() check on the initial URL. This vulnerability is fixed in 0.5.0b3.dev100.

Checking
Input Validation and Sanitization
Server-Side Request Forgery (SSRF)
Remote
1942
CVE-2026-45306
pyLoad allows authenticated users to steal session files for account takeover.

pyLoad is a free and open-source download manager written in Python. Prior to 0.5.0b3.dev100, the fix for CVE-2026-33509 prevents setting storage_folder inside PKGDIR or userdir, but does NOT protect the Flask session directory (/tmp/pyLoad/flask). An authenticated attacker can set storage_folder to the session directory and download session files of other users via /files/get/, leading to account takeover. This vulnerability is fixed in 0.5.0b3.dev100.

Checking
Input Validation and Sanitization
Path Traversal
Remote
1941
CVE-2026-45296
OpenReplay API allows cross-tenant access to session data via API keys.

OpenReplay is a self-hosted session replay suite. Prior to 1.26.0, OpenReplay's Python API exposes several app_apikey routes that trust a caller-provided projectKey after validating only that the API key itself is valid and that the target projectKey exists. The authorization flow does not verify that the authenticated API key and the requested project belong to the same tenant. Because the public tracker design exposes projectKey to browser-side code, an attacker who owns any valid API key for their own tenant can target another tenant's project by reusing that public projectKey. The vulnerable routes allow the attacker to enumerate victim user sessions and then retrieve sensitive session event data across the tenant boundary. This vulnerability is fixed in 1.26.0.

Checking
Authentication, Authorization, and Session Management
Insecure Direct Object References (IDOR)
Remote
1940
CVE-2026-48526
PyJWT allows using a public key as an HMAC secret, enabling signature forgery.

PyJWT is a JSON Web Token implementation in Python. Prior to 2.13.0, when the verifier is decoding JSON Web Tokens, while supporting both asymmetric and HMAC algorithms, the library does not validate use of JSON Web Keys in HMAC algorithm, allowing attacker to use the issuer public key as the secret key for HMAC algorithm. This vulnerability is fixed in 2.13.0.

Checking
Cryptographic
Cryptographic Implementation Error
Remote
1939
CVE-2026-48525
PyJWT allows unauthenticated DoS via crafted detached JWS payloads.

PyJWT is a JSON Web Token implementation in Python. From 2.8.0 to 2.12.1, when verifying detached JWS tokens using the unencoded-payload option ("b64": false, RFC 7797), PyJWT performs Base64URL decoding of the compact-serialization payload segment before enforcing the detached-payload rules. For b64=false, PyJWT later discards that decoded payload and replaces it with the caller-provided detached_payload. In practice, this turns the middle segment into an attacker-controlled โ€œwork amplifierโ€: a remote client can supply an arbitrarily large Base64URL payload segment that forces CPU work + memory allocations even if the signature is invalid. This creates an unauthenticated DoS vector against any endpoint that verifies detached JWS using PyJWT. This vulnerability is fixed in 2.13.0.

Timing/Serialization
Resource Management
Resource Exhaustion
Remote
1938
CVE-2026-48524
PyJWT allows DoS via unlimited JWKS requests from an unverified JWT `kid`.

PyJWT is a JSON Web Token implementation in Python. Prior to 2.13.0, PyJWKClient.get_signing_key() forces a fresh HTTP request to the JWKS endpoint for every JWT with an unknown kid value, with no rate limiting. Since kid comes from the unverified token header, an attacker can trigger unlimited outbound requests. The vulnerability surfaces only when a JWKS fetch fails; an attacker can attempt to provoke that with sustained unknown-kid traffic, but the outcome depends on upstream JWKS-endpoint behavior (rate limiting, transient errors) which is beyond the attacker's control. This vulnerability is fixed in 2.13.0.

Checking
Resource Management
Server-Side Request Forgery (SSRF)
Remote
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.

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