Sweet now harnesses generative AI to nail
business-critical cloud risks and reduce cloud Mean-Time-To-Respond
(MTTR) and Mean-Time-To-Contain (MTTC)
TEL
AVIV, Israel, July 31,
2024 /PRNewswire/ -- Sweet Security today
announced it has added generative artificial intelligence
(GenAI)-powered capabilities to its cloud runtime security suite.
Sweet users now have an upgraded ability for runtime risk
management and runtime response as they can classify workloads by
business impact and get granular incident response playbooks on the
fly. By integrating GenAI, Sweet enables security teams to act on
its runtime insights faster and reach Mean-Time-To-Contain (MTTC)
quicker than ever before. Sweet will be demonstrating its new
AI-powered capabilities at Black Hat, booth #3113.
Mandiant's 2024 m-trends report
underscores the importance of effective response to cyber attacks,
stating those with an existing incident response plan and broad
environmental monitoring are better prepared. Sweet's AI-generated
response plans ensure that SOC teams are well-prepared with
detailed instructions on how to quickly and safely intervene when
an incident occurs, in addition to insight on attacker tactics,
damage assessments, and the full attack path taken by the threat
actor.
Runtime Insights + GenAI = Lean, Mean, Response
Teams
Sweet's holistic approach to cloud security leverages
runtime insights to deliver comprehensive protection across all
layers of the stack—from cloud infrastructure assets, applications,
secrets, identities, APIs, and network interactions (Layer 7). This
enables it to detect sophisticated attacks that evade siloed
detection solutions. But complex risks require business focus and
agility -- resources in short supply when dealing with active
threats. Sweet's AI-powered risk management and response framework
help security teams nail business-critical risks and reduce the
Mean Time to Respond (MTTR) for incidents with the following new
features:
Workload classification -- for better vulnerability
prioritization: Using GenAI, security teams can now
classify workloads by business criticality. Adding to Sweet's
existing vulnerabilities filtering feature, which showcases if a
vulnerability is public facing/loaded/executed, etc., security
teams can now understand if the workload/s it impacts is business
critical. This enables security teams to prioritize the 1% of
active risks still in the queue.
Dynamically generated response playbooks -- to expedite
attack response and recovery: Sweet's AI-powered response
playbooks offer step-by-step instructions cyber analysts can
leverage to quickly get to the bottom of the incident, collect the
right artifacts needed for decision-making, and take action to
prevent escalation.
Sweet's GenAI - how it works under the hood
Sweet's
Large Language Models (LLMs) rely solely on models deployed
internally, so private data is not exposed to third-party services.
The LLMs are specifically trained with technical data across
cybersecurity, DevOps, and other relevant domains, taking in a very
broad context as an input to provide outputs that are hyper
relevant to the specific environment and situation, such as the
concrete code snippets to run. Once the context has been properly
aggregated, the next step is to break down the big use-case to a
chain of smaller increments that the LLM can correctly handle
without digressing into hallucinations.
"They say, attackers only need to be right once, but defenders
need to be right 100% of the time, but well-applied GenAI can level
the playing field," said Eyal
Fisher, co-founder and chief product officer, Sweet
Security. "That was our guiding light when we chose vulnerability
management and incident response as our initial use cases. We are
proud to provide AI functionality that enables security teams to
stay ahead of an adversary, because that's how you shut down an
attack."
About Sweet Security
Sweet Security offers
comprehensive runtime protection for cloud environments. Sweet's
solution shifts cloud security right, enabling security teams to
strategically address cloud risks as they unfold. Sweet's approach
analyzes behavioral anomalies, generating vital insights on
incidents, vulnerabilities, and non-human identities. Its
sensor-based, GenAI-infused technology and application profiling
cut through the cloud security noise and deliver actionable
recommendations on critical, real-time cloud risks. Privately
funded, Sweet is backed by Evolution Equity Partners, Munich Re
Ventures, Glilot Capital Partners, CyberArk Ventures and an elite
group of angel investors. For more information, please
visit http://sweet.security.
MEDIA CONTACT:
Elizabeth Safran
Looking Glass Public Relations for Sweet Security
381031@email4pr.com
408-348-1214
View original content to download
multimedia:https://www.prnewswire.com/news-releases/sweet-security-adds-generative-ai-to-its-cloud-runtime-security-suite-302210014.html
SOURCE Sweet Security