SciTokens is a reference library for generating and using SciTokens. Prior to version 1.9.6, the KeyCache class in scitokens was vulnerable to SQL Injection because it used Python's str.format() to construct SQL queries with user-supplied data (such as issuer and key_id). This allowed an attacker to execute arbitrary SQL commands against the local SQLite database. This issue has been patched in version 1.9.6.
Media · CVSS 4.8EPSS 0,39%Código de explotación públicoCorrección disponible
Apache Airflow Provider for Databricks: TLS Certificate Verification Disabled in Databricks Provider K8s Token Exchange
Improper Certificate Validation vulnerability in Apache Airflow Provider for Databricks. Provider code did not validate certificates for connections to Databricks back-end which could result in a man-of-a-middle attack that traffic is intercepted and manipulated or credentials exfiltrated w/o notice.
This issue affects Apache Airflow Provider for Databricks: from 1.10.0 before 1.12.0.
Users are recommended to upgrade to version 1.12.0, which fixes the issue.
Telnyx has malicious code in PyPI versions 4.87.1 and 4.87.2
## Summary
On March 27, 2026, a threat actor used compromised PyPI credentials to publish malicious versions 4.87.1 and 4.87.2 of the `telnyx` Python package directly to PyPI. These versions contain credential-stealing malware and were not published through the legitimate GitHub release pipeline.
## Exposure Window
| Version | Published (UTC) | Quarantined (UTC) | Exposure |
|---------|-----------------|-------------------|----------|
| 4.87.1 (broken) | 2026-03-27 03:51 | 2026-03-27 10:13 | 6h 22m |
| 4.87.2 (functional) | 2026-03-27 04:07 | 2026-03-27 10:13 | 6h 6m |
**Both versions were quarantined by PyPI at 2026-03-27 10:13 UTC.**
A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.
A path traversal vulnerability exists in the `extract_archive_to_dir` function within the `mlflow/pyfunc/dbconnect_artifact_cache.py` file of the mlflow/mlflow repository. This vulnerability, present in versions before v3.7.0, arises due to the lack of validation of tar member paths during extraction. An attacker with control over the tar.gz file can exploit this issue to overwrite arbitrary files or gain elevated privileges, potentially escaping the sandbox directory in multi-tenant or shared cluster environments.
Alta · CVSS 7.5EPSS 2,05%Código de explotación públicoCorrección disponible
Unauthenticated File Upload in parisneo/lollms
A vulnerability in parisneo/lollms, up to and including version 2.2.0, allows unauthenticated users to upload and process files through the `/api/files/extract-text` endpoint. This endpoint does not enforce authentication, unlike other file-related endpoints, and lacks the `Depends(get_current_active_user)` dependency. This issue can lead to denial of service (DoS) through resource exhaustion, information disclosure, and violation of the application's documented security policies.
Alta · CVSS 7.5EPSS 1,76%Código de explotación públicoCorrección disponible
Server-Side Request Forgery (SSRF) in parisneo/lollms
A Server-Side Request Forgery (SSRF) vulnerability exists in parisneo/lollms versions prior to 2.2.0, specifically in the `/api/files/export-content` endpoint. The `_download_image_to_temp()` function in `backend/routers/files.py` fails to validate user-controlled URLs, allowing attackers to make arbitrary HTTP requests to internal services and cloud metadata endpoints. This vulnerability can lead to internal network access, cloud metadata access, information disclosure, port scanning, and potentially remote code execution.
Insecure Direct Object Reference (IDOR) in parisneo/lollms
A critical security vulnerability in parisneo/lollms versions up to 2.2.0 allows any authenticated user to accept or reject friend requests belonging to other users. The `respond_request()` function in `backend/routers/friends.py` does not implement proper authorization checks, enabling Insecure Direct Object Reference (IDOR) attacks. Specifically, the `/api/friends/requests/{friendship_id}` endpoint fails to verify whether the authenticated user is part of the friendship or the intended recipient of the request. This vulnerability can lead to unauthorized access, privacy violations, and potential social engineering attacks. The issue has bee
OpenCC has an Out-of-bounds read when processing truncated UTF-8 input
### Summary
OpenCC versions before 1.2.0 contain two `CWE-125: Out-of-bounds Read` issues caused by length validation failures in UTF-8 processing. When handling malformed or truncated UTF-8 input, OpenCC trusted derived length values without enforcing the invariant that processed length must not exceed the remaining input buffer. This could result in out-of-bounds reads during segmentation or conversion.
### Details
Two independent code paths in OpenCC failed to enforce the invariant:
`matchedLength <= remainingLength`
Both paths assumed derived length values were valid and within input bounds, but did not validate that assumption again
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
pyLoad is a free and open-source download manager written in Python. Prior to version 0.5.0b3.dev97, PyLoad's download engine accepts arbitrary URLs without validation, enabling Server-Side Request Forgery (SSRF) attacks. An authenticated attacker can exploit this to access internal network services and exfiltrate cloud provider metadata. On DigitalOcean droplets, this exposes sensitive infrastructure data including droplet ID, network configuration, region, authentication keys, and SSH keys configured in user-data/cloud-init. Version 0.5.0b3.dev97 contains a patch.
python-ecdsa: Denial of Service via improper DER length validation in crafted private keys
The `ecdsa` PyPI package is a pure Python implementation of ECC (Elliptic Curve Cryptography) with support for ECDSA (Elliptic Curve Digital Signature Algorithm), EdDSA (Edwards-curve Digital Signature Algorithm) and ECDH (Elliptic Curve Diffie-Hellman). Prior to version 0.19.2, an issue in the low-level DER parsing functions can cause unexpected exceptions to be raised from the public API functions. `ecdsa.der.remove_octet_string()` accepts truncated DER where the encoded length exceeds the available buffer. For example, an OCTET STRING that declares a length of 4096 bytes but provides only 3 bytes is parsed successfully instead of being rej
Changedetection.io Discloses Environment Variables via jq env Builtin in Include Filters
changedetection.io is a free open source web page change detection tool. Prior to 0.54.7, the `jq:` and `jqraw:` include filter expressions allow use of the jq `env` builtin, which reads all process environment variables and stores them as the watch snapshot. An authenticated user (or unauthenticated user when no password is set, the default) can leak sensitive environment variables including `SALTED_PASS`, `PLAYWRIGHT_DRIVER_URL`, `HTTP_PROXY`, and any secrets passed as env vars to the container. Version 0.54.7 patches the issue.
Azure Data Explorer MCP Server: KQL Injection in multiple tools allows MCP client to execute arbitrary Kusto queries
Azure Data Explorer MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to execute KQL queries and explore Azure Data Explorer (ADX/Kusto) databases through standardized interfaces. Versions up to and including 0.1.1 contain KQL (Kusto Query Language) injection vulnerabilities in three MCP tool handlers: `get_table_schema`, `sample_table_data`, and `get_table_details`. The `table_name` parameter is interpolated directly into KQL queries via f-strings without any validation or sanitization, allowing an attacker (or a prompt-injected AI agent) to execute arbitrary KQL queries against the Azure Data Explorer cluster. C
Langflow: Authenticated Users Can Read, Modify, and Delete Any Flow via Missing Ownership Check
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.5.1, the `_read_flow` helper in `src/backend/base/langflow/api/v1/flows.py` branched on the `AUTO_LOGIN` setting to decide whether to filter by `user_id`. When `AUTO_LOGIN` was `False` (i.e., authentication was enabled), neither branch enforced an ownership check — the query returned any flow matching the given UUID regardless of who owned it. This allowed any authenticated user to read any other user's flow, including embedded plaintext API keys; modify the logic of another user's AI agents, and/or delete flows belonging to other users. The vuln
Langflow has Authenticated Code Execution in Agentic Assistant Validation
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.9.0, the Agentic Assistant feature in Langflow executes LLM-generated Python code during its validation phase. Although this phase appears intended to validate generated component code, the implementation reaches dynamic execution sinks and instantiates the generated class server-side. In deployments where an attacker can access the Agentic Assistant feature and influence the model output, this can result in arbitrary server-side Python execution. Version 1.9.0 fixes the issue.
Home Assistant is open source home automation software that puts local control and privacy first. Starting in version 2025.02 and prior to version 2026.01 the "remaining charge time"-sensor for mobile phones (imported/included from Android Auto it appears) is vulnerable cross-site scripting, similar to CVE-2025-62172. Version 2026.01 fixes the issue.
Home Assistant has stored XSS in Map-card through malicious device name
Home Assistant is open source home automation software that puts local control and privacy first. Starting in version 2020.02 and prior to version 2026.01, an authenticated party can add a malicious name to their device entity, allowing for Cross-Site Scripting attacks against anyone who can see a dashboard with a Map-card which includes that entity. It requires that the victim hovers over an information point. Version 2026.01 fixes the issue.
A weakness has been identified in huggingface smolagents 1.25.0.dev0. This affects the function evaluate_augassign/evaluate_call/evaluate_with of the file src/smolagents/local_python_executor.py of the component Incomplete Fix CVE-2025-9959. This manipulation causes code injection. It is possible to initiate the attack remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
Unauthorized Access to Tracing and Assessment Endpoints in mlflow/mlflow
In the latest version of mlflow/mlflow, when the `basic-auth` app is enabled, tracing and assessment endpoints are not protected by permission validators. This allows any authenticated user, including those with `NO_PERMISSIONS` on the experiment, to read trace information and create assessments for traces they should not have access to. This vulnerability impacts confidentiality by exposing trace metadata and integrity by allowing unauthorized creation of assessments. Deployments using `mlflow server --app-name=basic-auth` are affected.
Two telnyx versions published containing credential harvesting malware
After an API token exposure from an exploited Trivy dependency,
two new releases of `telnyx` were uploaded to PyPI containing automatically activated malware,
harvesting sensitive credentials and files, and exfiltrating to a remote API.
Compromised versions execute code during importing the `telnyx` module through modifications in `_client.py`.
The code downloads the next stages from endpoints on the host 83.142.209[.]203, encoded in WAV files.
On Windows hosts, the malicious executable is placed in
`%APPDATA%\Microsoft\Windows\Start Menu\Programs\Startup\msbuild.exe`
for persistence and executed.
On other systems, the payload is a Pyth