● Covered by 1 source · 1 reportMedium impact
Cisco Talos Deploys SnortML for Machine Learning Intrusion Detection
Cisco Talos launched SnortML, a machine learning detection engine integrated into Snort 3, to address gaps in traditional IDS. It allows for faster responses to novel exploits by processing data locally and issuing verdicts in under a millisecond.
Key points
- SnortML runs natively inside Snort 3.
- Processes data locally without cloud dependency.
- Designed to reduce response time to new exploits.
Introduction of SnortML
Cisco Talos introduced SnortML, a machine learning detection engine, in March 2024. This engine is integrated directly into Snort 3, enhancing its ability to detect novel exploits more swiftly than traditional methods.
Limitations of Traditional IDS
Traditional Intrusion Detection Systems (IDS) often leave a gap between the attack signature and the actual exploit behavior. This vulnerability occurs due to the time taken for researchers to develop rules for newly discovered exploits, leaving systems exposed during that window.
Functionality of SnortML
SnortML operates as part of the local processing pipeline within Snort, distinguishing it from generic anomaly detectors. It utilizes pre-trained TensorFlow models to classify threats with a response time of under one millisecond, allowing for rapid detection and response.
Agentic AI and Network Defense
The introduction of SnortML coincides with a broader trend of incorporating agentic AI into network security, which enhances proactive defense mechanisms. Together, these advancements represent a significant shift in how security operations are conducted, as they aim to bridge the exposure time gap in traditional detection methods.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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Reporting from
Cisco Talos launched SnortML, a machine learning detection engine integrated into Snort 3, to address gaps in traditional IDS. It allows for faster responses to novel exploits by processing data locally and issuing verdicts in under a millisecond.