Israeli startup Sweet Security has emerged
from stealth, launched a Cloud Runtime Security Suite, and
announced a $12 million seed funding round led by Glilot Capital
Partners with angel investors including Gerhard Eschenbach, and
Travis McPeak also participating.
The firm, headquartered in Tel Aviv, Israel, was founded in 2022
by Dror Kashti, CEO (former CISO of the Israel Defense Forces –
IDF) and Eyal Fisher, CPO (former head of the cyber department at
the IDF’s Unit 8200). They were joined by Orel Ben-Ishay, former
Head of the Cybersecurity R&D center at Unit 81.
The foundational principle underlying the Sweet Suite (we’ll
just call it Sweet) is that while it is important to shift security
left in securing development lifecycles, this must not be to the
detriment of looking right toward runtime. “Attacks only occur in
runtime,” says Sweet, “and companies require technological ‘boots
on the ground’ to detect them.” Existing detection tools, it adds,
either offer a limited analysis of cloud attacks or aren’t
optimized for the cloud. Most were developed to detect on-prem
attacks and are simply re-purposed to work on cloud attacks – but
cloud attacks differ in pace, volume, and operation.
The biggest problem is that many existing detection tools
provide too many ‘alerts’ with insufficient context. Alert fatigue is a genuine problem that can
lead to missed detections and response opportunities. Kashti cites
his inspiration for Sweet coming from frustration in his IDF CISO
role: “I was looking for a tool that would help me to detect and
respond to cloud attacks – and honestly, I couldn’t find a good
solution.”
The Sweet solution is claimed to be new on two primary counts.
According to VP of marketing, Noa Glumcher, firstly, it is claimed
to be the first solution that combines cloud runtime detection,
prevention, and response into a single solution suite. “Secondly,”
she adds, “we have a very unique, somewhat innovative framework for
detection.” This is a runtime sensor, described as ‘patent pending
automatic learning’ rather than machine learning in the now
traditional sense. “We start from a behavioral analysis baseline
that includes the business logic, the cloud context, and everything
specific to the customer’s environment. And we also learn the
anomalies.”
This starting point allows three things. “The first,” she
continued, “is to showcase everything within your cloud workloads,
all the assets, how they’re connected, all their map metadata and
all those connections. Another thing is to provide different levels
of response automation depending on the customer’s requirements.
The third is prioritization. Even before any attack, because we
have runtime visibility, we can locate, prioritize, and reduce CVEs
by up to 94%.”
The plan is to build on the possibilities provided by the sensor
and its detection capabilities (in part using the new funding).
While the sensor already provides contextualized visibility into
the system, Glumcher added, “We will provide a forensic analysis
for the incident response team so they can immediately see what has
happened – with an impact prediction and hardening recommendations
for the developers.” The effect is visibility into potential
compromise with remediation suggestions, visibility into an actual
compromise, and visibility into the potential effect of a
compromise.
“‘Cybersecurity’ and ‘delightful’ are not words that normally go
hand in hand, but we want our customers to use them in the same
sentence when talking about our solution,” said Kashti “We feel our
timing is right to make that happen. If SOC and IR teams don’t have
to constantly tune their security products or sift through
mountains of alerts, they’ll execute at a higher level, and they’ll
be happier. Cloud detection and response may be complex, but it
doesn’t have to be painful.”
The seed funding will be used to expand the development team,
further the company’s R&D efforts, open a US office, and expand
its global presence.
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