VAITP

Inclusion of functionality from untrusted control sphere in Visual Studio Code - Python extension allows an unauthorized attacker to bypass a security feature locally.

A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed.

A path traversal vulnerability exists in parisneo/lollms version 2.1.0, specifically in the SPA catch-all route implemented in `backend/routers/ui.py`. The vulnerability arises from the improper handling of user-controlled path input, which is directly joined into a filesystem path without sanitization or containment checks. URL-encoded dot-dot sequences (`%2e%2e`) bypass Starlette's built-in path normalization and are resolved by Python's `pathlib`, allowing an unauthenticated attacker to read arbitrary files on the server. This issue has been resolved in version 3.

pymdown-extensions is a collection of extensions for the Python Markdown library. In versions up to and including 11.0, four inline processors (caret, tilde, betterem, and magiclink) use regular expressions whose content groups can partition a run of delimiter characters in exponentially many ways, causing catastrophic backtracking. As a result, a single untrusted Markdown line under 50 bytes rendered with markdown.markdown() in each extension's default configuration drives the rendering thread into unbounded CPU usage that grows exponentially with input length, enabling an unauthenticated remote attacker who can submit Markdown to cause denial of service. The exposure is concrete for web applications that render user-supplied Markdown (comments, wikis, issue bodies, live preview), including any app using pymdownx.extra which bundles the vulnerable betterem default, as well as hosted docs/CI systems that build untrusted Markdown. The issue has been fixed in version 11.0.1.

PyMdown Extensions is a set of extensions for the Python-Markdown markdown project. In versions up to and including 10.21.3, the b64 extension is vulnerable to a path traversal that discloses arbitrary files: it inlines images referenced by <img src="..."> by joining the src onto the configured base_path with os.path.normpath and opening the result directly, without verifying that the resolved path stays inside base_path. As a result, an src containing ../ sequences or an absolute path reads a file outside base_path as long as it has an allowed image extension (.png, .jpg, .jpeg, .gif, .svg), and the file's contents are then base64-encoded into the rendered output, disclosing them. An application that renders untrusted Markdown with pymdownx.b64 enabled can therefore leak the contents of image-extension files readable by the process to whoever controls the Markdown or views the output, a targeted file-read bounded by the extension check. This issue has been fixed in version 11.0.

PraisonAI is a multi-agent teams system. In versions 3.9.26 through 4.6.57 of praiseonai and 0.12.12 through 1.6.57 of praiseonaiagents, the workflow "include" feature is vulnerable to code execution. Workflow._execute_include() implicitly imports and runs an included recipe's tools.py via a raw importlib.util.spec_from_file_location() and spec.loader.exec_module() call, without honoring the PRAISONAI_ALLOW_TEMPLATE_TOOLS/PRAISONAI_ALLOW_LOCAL_TOOLS autoload opt-in gates or routing through the centralized safe loader that protects the other tools.py autoload paths. As a result, a workflow that includes an attacker-controlled local recipe directory executes arbitrary module-level Python code during include setup, before any child workflow parsing or model call, and the same sink is reachable through the higher-level praisonai.recipe.run() recipe API. An attacker who can cause a victim process to run a workflow or recipe that includes an untrusted local recipe achieves arbitrary Python code execution as the PraisonAI process user, a variant that bypasses the hardening applied to the previously disclosed automatic tools.py RCE advisory family. This issue has been fixed in version 4.6.58 of praisonai and 1.6.58 of praisonaiagents.

IBM Langflow OSS 1.0.0 through 1.10.3 could allow an authenticated attacker to execute arbitrary code due to a cryptographic weakness in the custom component validation mechanism. When the optional hardening mode that restricts execution to trusted component templates is enabled, the application validates component code using a truncated SHA‑256 hash. Because the hash comparison relies on only a portion of the digest, an attacker can craft malicious component code that collides with a trusted template hash and bypasses validation. Successful exploitation allows the attacker to introduce and execute unauthorized Python code within the Langflow process, defeating the intended security control and potentially leading to full compromise of the affected instance.

IBM Langflow OSS 1.0.0 through 1.10.3 could allow an authenticated attacker to execute unintended code during Agentic Assistant validation due to improper handling of LLM‑generated components. The application executes model‑generated Python code in the backend during validation prior to user approval, which may allow an attacker to trigger side effects such as outbound network access, file system interaction, or data exfiltration with the privileges of the Langflow backend process.

IBM Langflow OSS 1.0.0 through 1.10.3, 1.0.0 through 1.10.3, 1.0.0 through 1.10.3, and 1.0.0 through 1.10.3 use Python's non-cryptographic random module for generating Fernet encryption keys from user secrets under 32 characters. The deterministic Mersenne Twister PRNG produces identical keys for identical seeds, allowing attackers to reproduce encryption keys and decrypt stored API keys and authentication tokens.

IBM Langflow OSS 1.0.0 through 1.10.3 could allow a remote authenticated attacker to execute arbitrary code due to improper validation of Python code during AST-based security scanning.