Detection as code: How to enhance your real-time threat detection
DaC can bolster the speed, accuracy, and scalability of your threat detection. Here are five essential steps to getting started.
Detection as code: How to enhance your real-time threat detection
Malicious attack method on hosted ML models now targets PyPI
RL researchers detected a new malicious campaign that exploits the Pickle file format on the Python Package Index.
How Spectra Assure's SaaSBOM Delivers Software Transparency
RL's SAFE report delivers insights into the APIs and services in your software, further enhancing transparency beyond a typical SBOM.
Boost VM security: 8 key strategies
Virtual-machine ubiquity requires rethinking traditional AppSec controls — and modernizing your approach. Here are essential considerations.
NIST Adversarial ML Guidance: How RL Can Secure Your Organization
New NIST guidance identifies ML challenges. Here’s why ReversingLabs Spectra Assure should be an essential part of your solution.
Backdoor implant discovered on PyPI posing as debugging utility
RL researchers detected a sophisticated, malicious package believed to be an ongoing campaign that may be linked to a hacktivist gang.
5 reasons you need an SaaSBOM
Here's why your organization should consider using SaaSBOMs, key challenges — and how to put CycloneDX's xBOM standard into action.
MCP is a powerful new AI coding technology: Understand the risks
Model Context Protocol makes agentic AI development easier by connecting data sources — but the risks are very real. Here's what you need to know.
From the Labs: YARA Rule for Detecting Conti
ReversingLabs’ YARA detection rule for Conti can help you detect this ransomware in your environment. We provide tools and information that you can use to spot CONTI at work in your environment.
Same name, different hack: PyPI package targets Solana developers
A new Python package revives the name of a malicious module to steal source code and secrets from blockchain developers’ machines.
Indirect prompt injection attacks target common LLM data sources
Malicious instructions buried in LLM sources such as documents can poison ML models. Here's how it works — and how to protect your AI systems.
SaaS risk is on the rise: 7 action items for better management
The rapid rise of SaaS apps has spawned new risks. One new hopeful stands out: The SaaSBOM. Here are key steps that help rein them in.
MIT researchers tame AI code with new controls
The sequential Monte Carlo method guides LLMs to produce code that plays by basic programming rules. Here's what you need to know.
Mobile and third-party risk: How legacy testing leaves you exposed
Without modern application security tooling, including binary analysis, the third-party risk management puzzle is incomplete.
Secrets leaks increase — and expand beyond the codebase
Leaks from GitHub and other repos are up, but collaboration tools such as Slack and Jira are now a major threat — and a serious blind spot.