AiStrike Emerges from Stealth to Solve Cloud Security Investigation and Response using AI-powered Automation
22 Mayo 2024 - 7:00AM
Business Wire
AiStrike, announced it emerged from stealth mode at the RSA
Conference 2024, where it showcased its solution aimed at
revolutionizing cloud security investigation and response using
AI-powered automation.
Cyberattacks targeting cloud infrastructure are on the rise.
Security operation teams are struggling to respond to cloud threats
in a timely manner. Too many alerts, not enough context, and
unclear cloud automations can quickly overwhelm people and tools.
AiStrike is using advanced behavior analytics and AI-guided
automation to prioritize, investigate, and neutralize threats in
cloud-native environments – in real-time. Early customers using
AiStrike are seeing immediate value with:
- 85% reduction in alert volume with behavior analytics-based
prioritization
- 70% improvement in mean time to respond (MTTR) with automation
playbooks from code-to-cloud
- 60% savings in analyst time with AI-guided investigation and
response
With over 20+ years of experience in security operations and
cloud technologies, AiStrike founders are well equipped to solve
the cloud security investigation and response problem.
“We are thrilled to announce AiStrike’s official launch out of
stealth,” said Nitin Agale, Founder and CEO of AiStrike.
“Traditional security investigation and response approaches are
ineffective to deal with the volume and complexity of threats in
cloud. This creates alert fatigue and piling backlogs of alerts.
Our solution automates alert enrichment, triage, and investigation,
and enables you to take proactive actions from code to cloud. The
RSA conference provided the perfect platform for us to unveil our
offering, and we are excited by the feedback of all those who saw
the tool in action.”
AiStrike's cloud-native security AI models are pre-trained based
on extensive and continuous attack simulations to provide
organizations guided automation to swiftly neutralize advanced and
emerging threats. When a new alert comes in, the solution
automatically:
- Enriches alert with context – AiStrike continuously
applies business, entity, threat, and infrastructure context to all
alerts, ensuring insights are always available with the most
up-to-date details.
- Prioritizes alert with analytics – In an unceasing sea
of alerts, AiStrike identifies high risk threat by applying ML and
AI analytics to baseline normal behavior and surface
anomalies.
- Investigates alert for root cause – AiStrike maps alerts
to artifact origins, identifying and assigning remediation
ownership. Security analyst can ask any clarification, deep dive,
or threat hunting question in plain English via our pre-trained AI
promptbook.
- Takes automated remediation action – AiStrike brings
environments back to a secure state by taking proactive and
automated actions on your behalf, including deep integration within
the CI/CD pipeline to take actions from code to cloud.
AiStrike integrates with all major cloud security tools and
cloud providers to support seamless deployment and quick
time-to-value, power charging your existing Cloud-Native
Application Protection Platform (CNAPP) and Cloud Security Posture
Management (CSPM) tools.
For more information about AiStrike and its cutting-edge
solution, please visit www.aistrike.com.
About AiStrike:
AiStrike solves cloud investigation and response with automation
and AI. We free you from alert fatigue. We reduce alert volume by
85%, by automatically enriching and prioritizing alerts for faster
MTTR and smarter decision-making. With AiStrike, you’ll get
real-time alert triage, guided investigation, and automated
response – all in one intuitive platform. Plus, we run specially
trained AI models locally to ensure your data remains private.
Ready to solve your cloud security operations? Visit
www.aistrike.com or follow us on LinkedIn.
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version on businesswire.com: https://www.businesswire.com/news/home/20240522292123/en/
Kayzad Vanskuiwalla Chief Product Officer, AiStrike
kayzad@aistrike.com