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Corelight
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@corelight_inc

Corelight

@corelight_inc
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
corelight.com
Joined October 2016
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  • Pinned
    @corelight_inc
    Corelight
    @corelight_inc
    Aug 31
    Effective agentic triage requires moving beyond black-box AI to deliver complete inspectability at every step of an investigation. In Episode 16 of Corelight DefeNDRs, Richard Bejtlich and Dave Getman discuss how Corelight Investigator synthesizes millions of network log lines
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  • @corelight_inc
    Corelight
    @corelight_inc
    15h
    Data moves across networks every day. Defenders still have to determine when that movement deserves investigation. Transfer volume, destinations, timing, and protocol behavior help defenders recognize suspicious data movement before relying on indicators alone. Explore how
    Graphic with a software interface with green binary code background and text saying, "Data movement doesn't always mean data theft. Context determines what deserves investigation." The Corelight logo is at the top left of the graphic.
    The image features the Corelight logo and the text: "Why investigators ask questions. Data moves every day. The investigation begins when the behavior no longer aligns with what is expected." The background is a digital-style design with binary code.
    The image displays a Corelight graphic. It features a list titled "What defenders monitor," including unusual data transfer volume, first-time destinations, cloud storage usage, protocol behavior, and transfer timing. A pink warning icon with an exclamation mark is at the bottom right. The background is dark with binary code.
    A  graphic from Corelight featuring the text: "Investigate suspicious data movement." It invites readers to "Learn how network evidence helps uncover potential data exfiltration" with a button labeled "Read the blog." The background displays a blurred screen with lines of computer code.
  • @corelight_inc
    Corelight
    @corelight_inc
    Sep 1
    In AI systems for network detection, minor adjustments to prompts, tool calls, or model parameters can cause silent signal drift, either missing critical intrusions or overloading analysts with noise. Developing trustworthy AI for network detection requires continuous evaluation
    Two individuals are examining data on a large transparent screen. The screen displays various graphs and data points. Text on the image reads: "AI system evaluation is about more than the model. Small changes throughout the system can lead to unexpected behavior, making continuous evaluation essential." Corelight Labs logo is in the corner.
    This image is a graphic with the title "AI system behavior emerges across multiple components:" followed by a list: Models, Prompts, Tools, Memory, Planning, Runtime context. A caption states, "A change to any one of them can change how the overall system behaves." The image features the Corelight Labs logo in the lower left corner, with a dark, abstract background.
    This image is a graphic with the title "In network detection, small mistakes can change the outcome" followed by "An agent gathers evidence, correlates activity, and reaches a verdict. Pulling the wrong log source or missing entity context can silently produce the wrong result" The image features the Corelight Labs logo in the lower left corner, with a dark, abstract background.
    Image graphic with a background of multiple computer screens displaying code. The text reads: "Evaluation should support continuous improvement. A strong evaluation framework helps teams: Detect regressions, Understand behavior, Improve AI systems with confidence." There's a prompt to "Read the blog" highlighted in green. Corelight Labs logo is at the bottom.
  • @corelight_inc
    Corelight
    @corelight_inc
    Aug 28
    Blocking standard AI sites barely scratches the surface of shadow AI. When sensitive data or proprietary code moves to unvetted LLM endpoints, SOC teams need to understand which services are in use, where traffic is going, and how usage is changing across the environment.
    Corelight promotional graphic featuring the text "Shadow AI isn't slowing down." The image includes a futuristic design with neon lights and a stylized star shape. 
The text below the featuring text reads "Governance starts with understanding what's already happening across your network. Read how Corelight's latest Sensor release expands Shadow AI detection and helps defenders turn network activity into actionable evidence." There's a prompt to read the blog post about Corelight's latest Sensor release.
  • @corelight_inc
    Corelight
    @corelight_inc
    Aug 27
    Lacking complete context while filtering through overwhelming alert volume continues to slow down SOC teams in complex environments. Jay Miller shares how a global cruise line transformed their investigation workflow using high-fidelity network telemetry, enabling faster
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