WordPress Title Experiments Free <9.0.1 - SQL Injection

WordPress Title Experiments Free plugin before 9.0.1 contains a SQL injection vulnerability. The plugin does not sanitize and escape the id parameter before using it in a SQL statement via the wpextitles AJAX action, available to unauthenticated users. An attacker can possibly obtain sensitive...

Do You Dare to Try Test-Driven Forensics? Increasing Trust in Desktop Forensics with ADARE

Digital forensic relies on validated tools and established procedures, yet the underlying operating systems, applications, and analysis tools evolve rapidly. This evolution can cause artifact behavior and tool outputs to drift, silently degrading repeatability and confidence in long-lived forensi...

Building an Adversarial Malware Dataset by Family and Type: Generation, Evasion, and Poisoning Evaluation

We present a dataset of adversarial malware samples derived from the public RawMal-TF collection of real-world malware binaries. Using a suite of adversarial malware generators, we construct two sets of adversarial PE files: 44,347 family-labelled samples and 33,596 type-labelled samples, achievi...

CVE-2025-67031

ORSEE Online Recruitment System for Economic Experiments 3.1.0 contains an authenticated Remote Code Execution vulnerability in the participant profile field processing subsystem. Certain field configurations accept values beginning with the prefix "func:" which are passed directly into an eval...

Online Recruitment System for Economic Experiments 安全漏洞

Online Recruitment System for Economic Experiments is an open-source online recruitment system for economic experiments developed by ORSEE. Version 3.1.0 of Online Recruitment System for Economic Experiments contains a security vulnerability. This vulnerability stems from the fact that values...

CVE-2025-67031

ORSEE 3.1.0 contains an authenticated Remote Code Execution vulnerability in the participant profile field processing subsystem. Certain field configurations accept values starting with the prefix "func:" , which are passed directly into an eval() call inside tagsets/participant.php and tagsets/o...

Convolutional-Neural-Networks for Deanonymisation of I2P Traffic

This study investigates the potential for deanonymizing services within the Invisible Internet Project I2P network through passive traffic analysis and machine learning techniques. The primary objective is to identify distinctive patterns in I2P traffic despite the encryption of its payload. To...

BIT-MLFLOW-2025-14279 DNS Rebinding Vulnerability in mlflow/mlflow

MLFlow versions up to and including 3.4.0 are vulnerable to DNS rebinding attacks due to a lack of Origin header validation in the MLFlow REST server. This vulnerability allows malicious websites to bypass Same-Origin Policy protections and execute unauthorized calls against REST endpoints. An...

CVE-2026-39934 Growth Experiments ReassignMenteesJob runs as an infinite loop

Loop with unreachable exit condition 'infinite loop' vulnerability in The Wikimedia Foundation Mediawiki - GrowthExperiments Extension allows Leveraging Time-of-Check and Time-of-Use TOCTOU Race Conditions. This issue was remediated only on the master branch...

NetSecBed: A Container-Native Testbed for Reproducible Cybersecurity Experimentation

Cybersecurity research increasingly depends on reproducible evidence, such as traffic traces, logs, and labeled datasets, yet most public datasets remain static and offer limited support for controlled re-execution and traceability, especially in heterogeneous multi-protocol environments. This...

SkillAttack: Automated Red Teaming of Agent Skills through Attack Path Refinement

LLM-based agent systems increasingly rely on agent skills sourced from open registries to extend their capabilities, yet the openness of such ecosystems makes skills difficult to thoroughly vet. Existing attacks rely on injecting malicious instructions into skills, making them easily detectable b...

ai-pocs

AI PoCs Workspace Personal workspace for AI/LLM experiments a...

Vertex AI Experiments Bucket Squatting Defensive Scanner

The Vertex AI Bucket Squatting Defensive Scanner is a security assessment tool designed to detect potential Google Cloud Storage bucket hijacking risks related to predictable naming patterns in Vertex AI experiment workflows. Instead of exploiting the vulnerability, this defensive version perform...

PT-2026-23821

We at Tachyon found an auth bypass in MLflow https://tachyon.so/blog/cve-2025-14297-mlflow-authorization-bypass: 1. Black-box scanners would need to discover the right users, roles, and state transitions, then generate specific request sequences that trigger a gap: a combinatorial problem that...

CVE-2026-2473

Predictable bucket naming in Vertex AI Experiments in Google Cloud Vertex AI from version 1.21.0 up to but not including 1.133.0 on Google Cloud Platform allows an unauthenticated remote attacker to achieve cross-tenant remote code execution, model theft, and poisoning via pre-creating predictabl...

CVE-2026-2473

Predictable bucket naming in Vertex AI Experiments in Google Cloud Vertex AI from version 1.21.0 up to but not including 1.133.0 on Google Cloud Platform allows an unauthenticated remote attacker to achieve cross-tenant remote code execution, model theft, and poisoning via pre-creating predictabl...

CVE-2026-2473 Bucket Squatting in Vertex AI Experiments leads to RCE and Model Theft.

Predictable bucket naming in Vertex AI Experiments in Google Cloud Vertex AI from version 1.21.0 up to but not including 1.133.0 on Google Cloud Platform allows an unauthenticated remote attacker to achieve cross-tenant remote code execution, model theft, and poisoning via pre-creating predictabl...

CVE-2026-2473 Bucket Squatting in Vertex AI Experiments leads to RCE and Model Theft.

Predictable bucket naming in Vertex AI Experiments in Google Cloud Vertex AI from version 1.21.0 up to but not including 1.133.0 on Google Cloud Platform allows an unauthenticated remote attacker to achieve cross-tenant remote code execution, model theft, and poisoning via pre-creating predictabl...

PT-2026-21291

Name of the Vulnerable Software and Affected Versions Google Cloud Vertex AI versions 1.21.0 through 1.132.9 Description A flaw exists in Vertex AI Experiments within Google Cloud Vertex AI that could allow a remote, unauthenticated attacker to execute code, steal models, and poison data. This is...

Server-side Request Forgery (SSRF)

Overview Affected versions of this package are vulnerable to Server-side Request Forgery SSRF via the HttpUriPlugin component when HTTP redirects are followed without re-validating the allowed URIs. An attacker can cause unauthorized network requests to internal services and inclusion of untruste...