Simply as triathletes know that peak efficiency requires greater than costly gear, cybersecurity groups are discovering that AI success relies upon much less on the instruments they deploy and extra on the info that powers them
The junk meals downside in cybersecurity
Think about a triathlete who spares no expense on tools—carbon fiber bikes, hydrodynamic wetsuits, precision GPS watches—however fuels their coaching with processed snacks and power drinks. Regardless of the premium gear, their efficiency will undergo as a result of their basis is essentially flawed. Triathletes see vitamin because the fourth self-discipline of their coaching that may have a big affect on efficiency and might even decide race outcomes.
At present’s safety operations facilities (SOCs) face the same problem. They’re investing closely in AI-powered detection programs, automated response platforms, and machine studying analytics—the equal of professional-grade triathlon tools. However they’re powering these refined instruments with legacy information feeds that lack the richness and context fashionable AI fashions have to carry out successfully.
Simply as a triathlete must grasp swimming, biking, and operating in seamless coordination, SOC groups should excel at detection, investigation, and response. Nonetheless, with out their very own “fourth self-discipline,” SOC analysts shall be working with sparse endpoint logs, fragmented alert streams, and information silos that do not talk, it is like attempting to finish a triathlon fueled solely by a bag of chips and a beer—regardless of how good your coaching or tools, you are not crossing the end line first. When you might load up on sugar and energy on race day to make sure you have the power to make it by means of, that isn’t a sustainable, long-term routine that may optimize your physique for the perfect efficiency.
The hidden value of legacy information diets
“We’re dwelling by means of the primary wave of an AI revolution, and thus far the highlight has targeted on fashions and purposes,” mentioned Greg Bell, Corelight chief technique officer. “That is sensible, as a result of the impacts for cyber protection are going to be large. However I feel there’s beginning to be a dawning realization that ML and GenAI instruments are gated by the standard of information they eat.”
This disconnect between superior AI capabilities and outdated information infrastructure creates what safety professionals at the moment are calling “information debt”—the gathered value of constructing AI programs on foundations that weren’t designed for machine studying consumption.
Conventional safety information usually resembles a triathlete’s coaching diary full of incomplete entries: “Ran at the moment. Felt okay.” It offers fundamental info however lacks the granular metrics, environmental context, and efficiency correlations that allow real enchancment. Legacy information feeds usually embody:
- Sparse endpoint logs that seize occasions however miss the behavioral context
- Alert-only feeds that inform you one thing occurred however not the total story
- Siloed information sources that may’t correlate throughout programs or time durations
- Reactive indicators that solely activate after harm is already finished with out historic views
- Unstructured codecs that require intensive processing earlier than AI fashions can analyze them
The adversary is already performance-enhanced
Whereas defenders battle with information that is nutritionally poor for AI consumption, attackers have optimized their method with the self-discipline of elite athletes. They’re leveraging AI to create adaptive assault methods which are quicker, cheaper, and extra exactly focused than ever earlier than by:
- Automating reconnaissance and exploit growth to speed up assault velocity
- Decreasing the fee per assault, rising potential risk quantity aster
- Personalizing approaches primarily based on AI-gathered intelligence to ship extra focused assaults
- Producing faster iteration and enchancment of ways primarily based on what’s working
In the meantime, many SOCs are nonetheless attempting to defend towards these AI-enhanced threats utilizing information equal to a Nineties coaching routine—with simply fundamental coronary heart charge info—when the competitors is utilizing complete efficiency analytics, environmental sensors, and predictive modeling.
This creates an escalating efficiency hole. As attackers develop into extra refined of their use of AI, the standard of defensive information turns into more and more crucial. Poor information does not simply decelerate detection—it actively undermines the effectiveness of AI safety instruments, creating blind spots that refined adversaries can exploit.
AI-ready information: the efficiency enhancement SOCs want
The answer lies in essentially reimagining safety information structure round what AI fashions truly have to carry out successfully. This implies transitioning from legacy information feeds to what may very well be known as “AI-ready” information—info that is structured, enriched, and optimized particularly for AI evaluation and automation.
AI-ready information shares traits with the excellent efficiency metrics that elite triathletes use to optimize their coaching. Simply as these athletes monitor all the things from energy output and cadence to environmental circumstances and restoration markers, AI-ready safety information captures not simply what occurred, however the full context surrounding every occasion.
This contains community telemetry that gives visibility earlier than encryption obscures the proof, complete metadata that reveals behavioral patterns, and structured codecs that AI fashions can instantly course of with out intensive preprocessing. It is information that is been particularly designed to feed the three crucial parts of AI-powered safety operations.
AI-driven risk detection turns into dramatically more practical when powered by forensic-grade community proof that features full context and real-time assortment throughout on-premise, hybrid, and multi-cloud environments. This permits AI fashions to determine delicate patterns and anomalies that might be invisible in conventional log codecs.
AI workflows rework the analyst expertise by offering expert-authored processes enhanced with AI-driven payload evaluation, historic context, and session-level summaries. That is equal to having a world-class coach who can immediately analyze efficiency information and supply particular, actionable steerage for enchancment.
AI-enabled ecosystem integrations make sure that AI-ready information flows seamlessly into current SOC instruments—SIEMs, SOAR platforms, XDR programs, and information lakes—with out requiring customized integrations or format conversions. It is mechanically appropriate with almost each instrument in an analyst’s arsenal.
The compound impact of superior information
The affect of transitioning to AI-ready information creates a compound impact throughout safety operations. Groups can correlate uncommon entry patterns and privilege escalations in ephemeral cloud environments, crucial for addressing cloud-native threats that conventional instruments miss. They achieve expanded protection for novel, evasive, and zero-day threats whereas enabling quicker growth of recent detections.
Maybe most significantly, analysts can shortly perceive incident timelines with out parsing uncooked logs, get plain-language summaries of suspicious behaviors throughout hosts and periods, and focus their consideration on precedence alerts with clear justifications for why every incident issues.
“Prime quality, context-rich information is the ‘clear gasoline’ AI wants to attain its full potential,” added Bell. “Fashions starved of high quality information will inevitably disappoint. As AI augmentation turns into the usual for each assault and protection, organizations that succeed would be the ones that perceive a elementary fact: on the earth of AI safety, you’re what you eat.”
The coaching resolution each SOC should make
As AI turns into commonplace for each assault and protection, AI-driven safety instruments can’t attain their potential with out the precise information. Organizations that proceed feeding these programs with legacy information might discover their vital funding in next-generation expertise underperforming towards more and more superior threats. People who acknowledge this is not about changing current safety investments — it is about offering them with the high-quality gasoline to ship on their promise — shall be positioned to unlock AI’s aggressive benefit.
Within the escalating battle towards AI-enhanced threats, peak efficiency actually begins with what you feed your engine.
For extra details about industry-standard safety information fashions that each one the foremost LLMs have already been educated on, go to www.corelight.com. Corelight delivers forensic-grade telemetry to energy SOC workflows, drive detection, and allow the broader SOC ecosystem.
