ContextHoundMar 13

ContextHound v1.8.0 is out 🎉

This release adds a Runtime Guard API - a lightweight wrapper that inspects your LLM calls in-process, before the request hits OpenAI or Anthropic.

Free and open-source. If this is useful to you or your team, a GitHub star or a small donation helps keep development going.
github.com/IulianVOStrut/ContextHound

#LLMSecurity #PromptInjection #CyberSecurity #OpenSource #AIRisk #AppSec #DevSecOps #GenAI #RuntimeSecurity #InfoSec #MLSecurity #ArtificialIntelligence

jpmellojrFeb 5
ML models are only as strong as the servers behind them. Check out “Vulnerable MCP Servers Lab: 9 ways to boost ML security" and lock down your AI stack: https://jpmellojr.blogspot.com/2026/02/vulnerable-mcp-servers-lab-9-ways-to.html #MLSecurity #AppSec #CyberSecurity #AI #MCPlab
Tanisha L. TurnerJan 5

ThreatSentry AI: A threat hunting dashboard that utilizes ML and determines risk assessment by vulnerability identification of data

Check ✅️ it out:

https://github.com/EclipseManic/ThreatSentry-AI

#threathunting #mlsecurity #threatdetection #aisecurity

GitHub - EclipseManic/ThreatSentry-AI: ThreatSentry AI is an intelligent threat hunting dashboard that leverages machine learning to proactively identify and prioritize risks in your network. It automates the process of collecting device information, enriching it with vulnerability data, and assessing risk levels, enabling security teams to focus on the most critical threats.

ThreatSentry AI is an intelligent threat hunting dashboard that leverages machine learning to proactively identify and prioritize risks in your network. It automates the process of collecting devic...

GitHub
Manuel BisseyNov 26

☝️New research shows SLMS can detect phishing websites with high accuracy — machine learning is becoming a sharper shield against social engineering. 🤖🛡️ #PhishingDetection #MLSecurity

https://www.helpnetsecurity.com/2025/11/26/research-slms-website-phishing-detection/

Small language models step into the fight against phishing sites - Help Net Security

Small language models (SLMs) offer new ways to spot phishing on websites and give teams room to improve detection on their own systems.

Help Net Security
ScanMalware.comOct 3

🔍 Web Malware Scan Results

Website: portwashingtonnorth.gov
Security Verdict: LOW RISK

Full analysis & details:
https://scanmalware.com/scan/ccf5e9b4-816f-4d1a-a603-3623e21ecd70

#VulnerabilityManagement #CyberResilience #ZeroDay #MLSecurity

Security Scan: Village of Port Washington North - Official W

⚡ Medium Risk - https://portwashingtonnorth.gov/

ScanMalware.com
ScanMalware.comOct 3

🔍 Web Malware Scan Results

Website: marylandhealthconnection.gov
Security Verdict: LOW RISK

Full analysis & details:
https://scanmalware.com/scan/213c99d9-1adf-4996-a249-916d7b061f93

#CyberSecurity #VulnerabilityManagement #CyberDefense #DataSecurity #MLSecurity

ScanMalware.comOct 3

🔍 Web Malware Scan Results

Website: www.interno.gov.it
Security Verdict: LOW RISK

Full analysis & details:
https://scanmalware.com/scan/1704904a-4361-4886-809b-c99dd4445f76

#CISO #MLSecurity #VulnerabilityManagement #DevSecOps #ThreatHunting

ScanMalware.comOct 3

🔍 Web Malware Scan Results

Website: adaircountymissouri.com
Security Verdict: LOW RISK

Full analysis & details:
https://scanmalware.com/scan/fdbe4669-0f0f-4b0f-823c-8f0ab936e5a5

#ThreatIntel #WebMalware #MLSecurity #ThreatHunting

Security Scan: Adair County Missouri Government Government

⚡ Medium Risk - https://adaircountymissouri.com/

ScanMalware.com
Show threadAnnual Computer Security Applications ConferenceSep 18, 2025
Launching the session was Li et al.'s "FedCAP: Robust Federated Learning via Customized Aggregation and Personalization," showing a novel solution tackling data heterogeneity and Byzantine threats. (https://www.acsac.org/2024/program/final/s336.html) 2/6
#MLSecurity #CyberSecurity #AI
Show threadAnnual Computer Security Applications ConferenceAug 7, 2025
Ending the session, we saw Ferens et al.'s "Securing PUFs via a Predictive Adversarial ML System by Modeling of Attackers" highlighting advances in defending #IoT devices against ML-based #PUF attacks. (https://www.acsac.org/2024/program/final/s179.html) 6/6
#Cybersecurity #MLSecurity