Corelight transforms network data into definitive evidence, powering AI-driven detection and expert-authored workflows, and enabling the AI SOC ecosystem.

San Francisco and Columbus
Joined October 2016
Corelight’s Threat R&D team was building detections for DFS-based coercion attacks when a test server crashed. The crash in mup.sys uncovered CVE-2026-70111, a null dereference crash causing denial-of-service affecting Windows Server 2019, 2022, and 2025. An attacker can coerce an affected server to connect to a rogue server, which returns a malformed DFS referral response. When mup.sys processes it, the server crashes. The exchange runs over internal SMB traffic, so detection requires east-west coverage. The research explains how Suricata identifies the malformed response and Zeek conn.log records sessions going silent and connections resetting after reboot. Read the research 👉 corelight.com/blog/cve-2026-…
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Adapting to the fast changes in cybersecurity requires more than learning new technology. Community makes a difference. While technology provides the foundation, real-world context gained from face-to-face community connection is what shapes effective, adaptable problem-solving. Alissar Abdin, Strategic Account Development Representative, tells us why stepping away from the screen and connecting with peers has been the most important lesson of their career. #CybersecurityAwarenessMonth
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Identity is important, but it can’t give defenders the full picture of attacker intent. Ali Islam Khan, Vice President of Corelight Labs, explains why network behavior can help teams audit what an identity is actually doing, especially as nation-state actors increasingly use open-source tools and living-off-the-land techniques. That same data foundation matters as AI becomes part of more security workflows. Without high-fidelity data, the quality of what security teams get back from AI suffers. Watch now 👇
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What can an AI agent answer when the evidence it needs isn’t in the data? In Corelight’s research, switching between the tested frontier models made relatively little difference to performance on a capture-the-flag exercise. Holding the model fixed and changing the network data produced much larger differences in the questions the agent could answer. Corelight co-founder and Chief Strategy Officer Greg Bell joins James Wilson on Risky Biz to discuss the findings and why data needs to be a first-class citizen when designing an agentic SOC. Listen to the conversation 👉 youtube.com/watch?v=S1GjydKz…
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When your environment negotiates encryption using both legacy defaults and new Post-Quantum Cryptography ciphers, routine traffic patterns suddenly look anomalous. Attempting to decrypt all network traffic at scale quickly becomes an expensive compute bonfire. For most high-throughput environments, trying to inspect every encrypted payload simply isn't scalable or cost-effective. Corelight researcher Josh Porto shows how defenders maintain high-confidence visibility through the PQC transition without relying on line-rate decryption. Discover how investigators maintain clear network evidence through changing encryption standards. Explore the analysis: corelight.com/blog/pqc-the-u…
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The typical small PCAP + BTest approach works well for testing Zeek packages, but sometimes a PCAP isn’t available, shareable, or practical for the behavior you need to test. Here is how detection engineers can use BTest and the assert statement introduced in Zeek 6.1.0 to write script-layer unit tests for auxiliary functions. 🧵⬇️
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BTest doesn’t have a script-layer unit testing library like pytest, but its basic functions can be emulated using assert, introduced in Zeek 6.1.0. Using assert makes the intent of the test clear and, when a test fails, clearly flags which test case failed.
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This gives Zeek package developers a straightforward way to unit test auxiliary functions without having to construct PCAPs for every test case. How is your team currently handling unit testing for custom Zeek scripts and packages?
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Attackers increasingly use legitimate admin utilities and valid API keys to map systems and escalate privilege after an initial breach. Signature-based EDR can treat this as normal admin activity, while automated attacks can move faster than human operators can triage an alert. Chrissie Padilla, Manager of Network Security Training, shares what security teams should be paying more attention to right now. #CybersecurityAwarenessMonth
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Asking an AI assistant about a suspicious IP usually yields basic entity summaries. Arming AI agents with custom skills and protocol field logic allows SOC teams to turn broad log queries into deep, automated forensic investigations.
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95% vs. 26%. In a Volt Typhoon-inspired CTF, GPT-5.4 answered 95% of investigative questions using Corelight data, compared with 26% using NetFlow. The model did not change. The evidence did. The finding points to a knowledge ceiling for AI-assisted investigations: when the required evidence is missing, a stronger model cannot recover it. See the findings: explore.corelight.com/provab…
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What the network means has changed. Cloud properties, remote workforces, and AI workloads have expanded the surface defenders need to understand. At the same time, network data is increasingly being consumed by systems and agents alongside analysts. Corelight Field CTO Vince Stoffer explains why that makes network evidence and interoperability increasingly important, and why security leaders need to think about the modern SOC as a whole system instead of a collection of isolated tools. Watch now 👇
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Opaque AI alerts create additional work for security teams because analysts have to manually double-check unverified conclusions. Delivering transparent, explainable AI workflows in the SOC requires pairing automated findings with the underlying network evidence used to generate them. 🧵👇
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Defensible AI triage must expose its complete reasoning chain directly to defenders. By presenting the finding, the supporting evidence, and the recommended next move in a transparent interface, Corelight ensures analysts can rapidly validate automated conclusions and act with confidence.
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Grounding AI investigations in transparent workflows allows security teams to validate automated decisions rapidly, build trust in agentic outputs, and execute response actions with confidence. How does your team currently verify automated AI conclusions before acting on an alert? Tell us below.
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Corelight has been named a winner at The 2026 A.I. Awards, taking home Best Use of AI in Cybersecurity! 🏆 As AI becomes part of more security workflows, we're focused on helping defenders investigate faster, work from high-quality network evidence, and understand how conclusions are reached. We're proud to see this work recognized and grateful to the teams across Corelight who continue to make it possible. See the full list of winners: cloud-awards.com/ai-awards/2…
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Identity-based attacks become especially difficult to spot when an attacker looks like a legitimate user. Once an attacker gains access, the challenge shifts from access control to seeing what that apparently legitimate identity is doing across the network. Tracey Conn, AVP, SLED, shares the one thing security teams should be paying attention to right now. #CybersecurityAwarenessMonth
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When a new vulnerability is disclosed, the evidence needed to investigate it may already be in your network logs. In an offline replay of proof-of-concept traffic for Citrix NetScaler CVE-2026-88772, Zeek's existing DTLS analyzer recorded a handshake length mismatch. For defenders retaining those logs, that creates an opportunity to search historical traffic, including activity recorded before the vulnerability was disclosed. Corelight Labs researcher Deepali Prasad walks through how to search for the diagnostic and correlate findings with connection records and appliance evidence. A matching diagnostic warrants investigation, but doesn't confirm compromise. Read the analysis: corelight.com/blog/hunting-c…
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With AI systems transitioning into everyday workflows, securing them requires rethinking how we monitor their infrastructure. Without clear insight into how these systems exchange data, security teams can risk running blind. Alissar Abdin, Strategic Account Development Representative, shares why protocol-level visibility is essential to building an effective AI security posture. #CybersecurityAwarenessMonth
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