Unsafe URL path construction in LangGraph SDK allows for path traversal.
LangGraph Python SDK is used to connect to running LangGraph API servers, manage assistants, threads and stream runs from Python applications. Versions 0.3.14 and prior have unsafe URL path construction through unsanitized caller-supplied identifier values used in HTTP request paths for resource operations. Without sanitization of those values, identifiers that contain characters with special meaning in URL paths could cause the resulting request to address a different resource (and potentially a different resource type) than the SDK method's call site indicates. In deployments where the SDK receives identifier values that originate from untrusted sources, this could result in unintended access, modification, or deletion of resources beyond the calling user's authorization scope. This issue is most consequential in deployments that forward end-user-supplied values directly into SDK identifier parameters without first validating them against an expected format (such as a UUID), and rely on URL-prefix-based authorization at an upstream layer (reverse proxy, edge gateway, WAF), where the authorization decision is made on the SDK call's intended path rather than on the final delivered request path. The issue has been fixed in version 0.3.15.
OpenClaw: .env file injection in CLOUDSDK_PYTHON allows code execution.
OpenClaw before 2026.5.2 contains an environment variable injection vulnerability allowing workspace .env files to influence Python runtime selection through CLOUDSDK_PYTHON during Gmail setup gcloud execution. Attackers with repository access can manipulate the CLOUDSDK_PYTHON variable to execute setup through unintended local Python paths, potentially enabling arbitrary code execution.
Insecure deserialization in LangGraph checkpoints may lead to code execution.
LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). In versions 4.1.0 and prior, the JsonPlusSerializer can reconstruct Python objects from JSON checkpoint payloads. Under conditions where someone could modify checkpoint bytes at rest in the backing store, the deserialization path could reconstruct objects beyond what the application expects, which could in turn result in code execution at checkpoint load time. This is a defense-in-depth issue. The affected behavior is reachable only when checkpoint bytes at rest in the backing store can be modified by an unauthorized party. In most deployments that prerequisite already implies a serious incident; the additional concern is turning "checkpoint-store write access" into code execution in the application runtime. This issue has been fixed in version 4.1.1.
A remote SSRF vulnerability in python-utcp 1.1.0's websocket component.
A vulnerability was detected in universal-tool-calling-protocol python-utcp 1.1.0. This affects an unknown function of the component utcp-gql/utcp-websocket. Performing a manipulation results in server-side request forgery. The attack can be initiated remotely. The exploit is now public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
Kitty < 0.47.0 allows remote code execution via crafted terminal output.
Kitty is a cross-platform GPU based terminal. In versions prior to 0.47.0, a program able to write bytes to a kitty terminal โ a remote SSH peer, a downloaded file viewed with `cat`, a log line, an email body rendered in `less`, an issue body in a TUI, etc. โ can cause kitty to execute attacker-supplied Python inside the running kitty process, with the user's full privileges. There is no approval prompt, no remote-control permission requirement, no shell-integration interaction, no clipboard touch, and no editor interaction. Version 0.47.0 fixes the issue.
Authenticated RCE in ChromaDB via malicious model with trust_remote_code.
A code injection vulnerability in version 0.4.17 or later of the ChromaDB Python project allows an authenticated attacker to run arbitrary code on the server by sending a malicious model repository and trust_remote_code set to true in theย /api/v2/tenants/default_tenant/databases/default_database/collections/{collection_id} if they have the UPDATE_COLLECTION permission.
Authorization bypass in ChromaDB V1 endpoints due to None tenant/DB values.
All V1 collection-level endpoints in ChromaDB's Python project pass None for the tenant and database to the authorization layer, allowing attackers to bypass authorization controls by using the V1 endpoints.
ChromaDB RBAC fails to check permission scope, allowing cross-tenant actions.
The SimpleRBACAuthorizationProvider authorization provider in versions 0.5.0 or later of the ChromaDB Python project evaluates whether a user holds a given permission but never checks which tenant, database, or collection that permission applies to allowing users to perform cross tenant actions.
ChromaDB auth flaw allows users to read/write data across all tenants.
A lack of authorization validation in version 0.4.17 or later of the ChromaDB Python project allows any authenticated users to arbitrarily read, write, update, or delete data in any tenant's collection regardless of which tenant they belong to.
Vim Python omni-completion allows code execution from malicious buffers.
Vim is an open source, command line text editor. Prior to version 9.2.0597, Vim's Python omni-completion executes reconstructed function and class definitions from the current buffer with exec() as part of populating the completion dictionary. Python evaluates function default values, parameter annotations, and class base expressions at definition time, so a hostile buffer can execute attacker-controlled Python expressions during omni-completion. The existing g:pythoncomplete_allow_import mitigation (GHSA-52mc-rq6p-rc7c) does not cover this path, because the attacker-controlled code is not a harvested import/from statement. This issue has been patched in version 9.2.0597.
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.
The supreme art of war is to subdue the enemy without fighting.
Sun Tzu – “The Art of War”
:: Shaping the future through research and ingenuity ::
