cybersecurity
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Confluera snags $9M Series A to help stop cyberattacks in real time
Just yesterday, we experienced yet another major breach when Capital One announced it had been hacked and years of credit card application information had been stolen. Another day, another hack, but the question is how can companies protect themselves in the face of an onslaught of attacks. Confluera, a Palo Alto startup, wants to help with a new tool that purports to stop these kinds of attacks in real time.
Today the company, which launched last year, announced a $9 million Series A investment led by Lightspeed Venture Partners . It also has the backing of several influential technology execs, including John W. Thompson, who is chairman of Microsoft and former CEO at Symantec; Frank Slootman, CEO at Snowflake and formerly CEO at ServiceNow; and Lane Bess, former CEO of Palo Alto Networks.
What has attracted this interest is the company’s approach to cybersecurity. “Confluera is a real-time cybersecurity company. We are delivering the industry’s first platform to deterministically stop cyberattacks in real time,” company co-founder and CEO Abhijit Ghosh told TechCrunch.
To do that, Ghosh says, his company’s solution watches across the customer’s infrastructure, finds issues and recommends ways to mitigate the attack. “We see the problem that there are too many solutions which have been used. What is required is a platform that has visibility across the infrastructure, and uses security information from multiple sources to make that determination of where the attacker currently is and how to mitigate that,” he explained.
Microsoft chairman John Thompson, who is also an investor, says this is more than just real-time detection or real-time remediation. “It’s not just the audit trail and telling them what to do. It’s more importantly blocking the attack in real time. And that’s the unique nature of this platform, that you’re able to use the insight that comes from the science of the data to really block the attacks in real time.”
It’s early days for Confluera, as it has 19 employees and three customers using the platform so far. For starters, it will be officially launching next week at Black Hat. After that, it has to continue building out the product and prove that it can work as described to stop the types of attacks we see on a regular basis.
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The right way to do AI in security
Artificial intelligence applied to information security can engender images of a benevolent Skynet, sagely analyzing more data than imaginable and making decisions at lightspeed, saving organizations from devastating attacks. In such a world, humans are barely needed to run security programs, their jobs largely automated out of existence, relegating them to a role as the button-pusher on particularly critical changes proposed by the otherwise omnipotent AI.
Such a vision is still in the realm of science fiction. AI in information security is more like an eager, callow puppy attempting to learn new tricks – minus the disappointment written on their faces when they consistently fail. No one’s job is in danger of being replaced by security AI; if anything, a larger staff is required to ensure security AI stays firmly leashed.
Arguably, AI’s highest use case currently is to add futuristic sheen to traditional security tools, rebranding timeworn approaches as trailblazing sorcery that will revolutionize enterprise cybersecurity as we know it. The current hype cycle for AI appears to be the roaring, ferocious crest at the end of a decade that began with bubbly excitement around the promise of “big data” in information security.
But what lies beneath the marketing gloss and quixotic lust for an AI revolution in security? How did AL ascend to supplant the lustrous zest around machine learning (“ML”) that dominated headlines in recent years? Where is there true potential to enrich information security strategy for the better – and where is it simply an entrancing distraction from more useful goals? And, naturally, how will attackers plot to circumvent security AI to continue their nefarious schemes?
How did AI grow out of this stony rubbish?
The year AI debuted as the “It Girl” in information security was 2017. The year prior, MIT completed their study showing “human-in-the-loop” AI out-performed AI and humans individually in attack detection. Likewise, DARPA conducted the Cyber Grand Challenge, a battle testing AI systems’ offensive and defensive capabilities. Until this point, security AI was imprisoned in the contrived halls of academia and government. Yet, the history of two vendors exhibits how enthusiasm surrounding security AI was driven more by growth marketing than user needs.
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Huawei opens a cybersecurity transparency center in the heart of Europe
5G kit maker Huawei opened a Cyber Security Transparency center in Brussels yesterday as the Chinese tech giant continues to try to neutralize suspicion in Western markets that its networking gear could be used for espionage by the Chinese state.
Huawei announced its plan to open a European transparency center last year but giving a speech at an opening ceremony for the center yesterday the company’s rotating CEO, Ken Hu, said: “Looking at the events from the past few months, it’s clear that this facility is now more critical than ever.”
Huawei said the center, which will demonstrate the company’s security solutions in areas including 5G, IoT and cloud, aims to provide a platform to enhance communication and “joint innovation” with all stakeholders, as well as providing a “technical verification and evaluation platform for our
customers”.
“Huawei will work with industry partners to explore and promote the development of security standards and verification mechanisms, to facilitate technological innovation in cyber security across the industry,” it said in a press release.
“To build a trustworthy environment, we need to work together,” Hu also said in his speech. “Both trust and distrust should be based on facts, not feelings, not speculation, and not baseless rumour.
“We believe that facts must be verifiable, and verification must be based on standards. So, to start, we need to work together on unified standards. Based on a common set of standards, technical verification and legal verification can lay the foundation for building trust. This must be a collaborative effort, because no single vendor, government, or telco operator can do it alone.”
The company made a similar plea at Mobile World Congress last week when its rotating chairman, Guo Ping, used a keynote speech to claim its kit is secure and will never contain backdoors. He also pressed the telco industry to work together on creating standards and structures to enable trust.
“Government and the mobile operators should work together to agree what this assurance testing and certification rating for Europe will be,” he urged. “Let experts decide whether networks are safe or not.”
Also speaking at MWC last week the EC’s digital commissioner, Mariya Gabriel, suggested the executive is prepared to take steps to prevent security concerns at the EU Member State level from fragmenting 5G rollouts across the Single Market.
She told delegates at the flagship industry conference that Europe must have “a common approach to this challenge” and “we need to bring it on the table soon”.
Though she did not suggest exactly how the Commission might act.
A spokesman for the Commission confirmed that EC VP Andrus Ansip and Huawei’s Hu met in person yesterday to discuss issues around cybersecurity, 5G and the Digital Single Market — adding that the meeting was held at the request of Hu.
“The Vice-President emphasised that the EU is an open rules based market to all players who fulfil EU rules,” the spokesman told us. “Specific concerns by European citizens should be addressed. We have rules in place which address security issues. We have EU procurement rules in place, and we have the investment screening proposal to protect European interests.”
“The VP also mentioned the need for reciprocity in respective market openness,” he added, further noting: “The College of the European Commission will hold today an orientation debate on China where this issue will come back.”
In a tweet following the meeting Ansip also said: “Agreed that understanding local security concerns, being open and transparent, and cooperating with countries and regulators would be preconditions for increasing trust in the context of 5G security.”
Met with @Huawei rotating CEO Ken Hu to discuss #5G and #cybersecurity.
Agreed that understanding local security concerns, being open and transparent, and cooperating with countries and regulators would be preconditions for increasing trust in the context of 5G security. pic.twitter.com/ltATdnnzvL
— Andrus Ansip (@Ansip_EU) March 4, 2019
Reuters reports Hu saying the pair had discussed the possibility of setting up a cybersecurity standard along the lines of Europe’s updated privacy framework, the General Data Protection Regulation (GDPR).
Although the Commission did not respond when we asked it to confirm that discussion point.
GDPR was multiple years in the making and before European institutions had agreed on a final text that could come into force. So if the Commission is keen to act “soon” — per Gabriel’s comments on 5G security — to fashion supportive guardrails for next-gen network rollouts a full blown regulation seems an unlikely template.
More likely GDPR is being used by Huawei as a byword for creating consensus around rules that work across an ecosystem of many players by providing standards that different businesses can latch on in an effort to keep moving.
Hu referenced GDPR directly in his speech yesterday, lauding it as “a shining example” of Europe’s “strong experience in driving unified standards and regulation” — so the company is clearly well-versed in how to flatter hosts.
“It sets clear standards, defines responsibilities for all parties, and applies equally to all companies operating in Europe,” he went on. “As a result, GDPR has become the golden standard for privacy protection around the world. We believe that European regulators can also lead the way on similar mechanisms for cyber security.”
Hu ended his speech with a further industry-wide plea, saying: “We also commit to working more closely with all stakeholders in Europe to build a system of trust based on objective facts and verification. This is the cornerstone of a secure digital environment for all.”
Huawei’s appetite to do business in Europe is not in doubt, though.
The question is whether Europe’s telcos and governments can be convinced to swallow any doubts they might have about spying risks and commit to working with the Chinese kit giant as they roll out a new generation of critical infrastructure.
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Backed by Benchmark, Blue Hexagon just raised $31 million for its deep learning cybersecurity software
Nayeem Islam spent nearly 11 years with chipmaker Qualcomm, where he founded its Silicon Valley-based R&D facility, recruited its entire team and oversaw research on all aspects of security, including applying machine learning on mobile devices and in the network to detect threats early.
Islam was nothing if not prolific, developing a system for on-device machine learning for malware detection, libraries for optimizing deep learning algorithms on mobile devices and systems for parallel compute on mobile devices, among other things.
In fact, because of his work, he also saw a big opportunity in better protecting enterprises from cyberthreats through deep neural networks that are capable of processing every raw byte within a file and that can uncover complex relations within data sets. So two years ago, Islam and Saumitra Das, a former Qualcomm engineer with 330 patents to his name and another 450 pending, struck out on their own to create Blue Hexagon, a now 30-person Sunnyvale, Calif.-based company that is today disclosing it has raised $31 million in funding from Benchmark and Altimeter.
The funding comes roughly one year after Benchmark quietly led a $6 million Series A round for the firm.
So what has investors so bullish on the company’s prospects, aside from its credentialed founders? In a word, speed, seemingly. According to Islam, Blue Hexagon has created a real-time, cybersecurity platform that he says can detect known and unknown threats at first encounter, then block them in “sub seconds” so the malware doesn’t have time to spread.
The industry has to move to real-time detection, he says, explaining that four new and unique malware samples are released every second, and arguing that traditional security methods can’t keep pace. He says that sandboxes, for example, meaning restricted environments that quarantine cyberthreats and keep them from breaching sensitive files, are no longer state of the art. The same is true of signatures, which are mathematical techniques used to validate the authenticity and integrity of a message, software or digital document but are being bypassed by rapidly evolving new malware.
Only time will tell if Blue Hexagon is far more capable of identifying and stopping attackers, as Islam insists is the case. It is not the only startup to apply deep learning to cybersecurity, though it’s certainly one of the first. Critics, some who are protecting their own corporate interests, also worry that hackers can foil security algorithms by targeting the warning flags they look for.
Still, with its technology, its team and its pitch, Blue Hexagon is starting to persuade not only top investors of its merits, but a growing — and broad — base of customers, says Islam. “Everyone has this issue, from large banks, insurance companies, state and local governments. Nowhere do you find someone who doesn’t need to be protected.”
Blue Hexagon can even help customers that are already under attack, Islam says, even if it isn’t ideal. “Our goal is to catch an attack as early in the kill chain as possible. But if someone is already being attacked, we’ll see that activity and pinpoint it and be able to turn it off.”
Some damage may already be done, of course. It’s another reason to plan ahead, he says. “With automated attacks, you need automated techniques.” Deep learning, he insists, “is one way of leveling the playing field against attackers.”
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Goldman Sachs leads $8M round in cybersecurity skills platform Immersive Labs
Immersive Labs, a cybersecurity skills platform founded by former GCHQ researcher James Hadley, has raised $8 million in Series A funding. Leading the round is Goldman Sachs, with participation from a number of unnamed private investors.
Operating in the cybersecurity training space, Immersive Labs helps enterprise IT and other cybersecurity teams acquire the latest security skills by combining up to date threat data with what is described as “gamified” learning. This sees the startup use real-time feeds of the latest attack techniques, hacker psychology and technological vulnerabilities to quickly create “cyber war games” for IT and security teams to learn from.
The idea is that the platform can up-skill people within hours of a threat emerging, in addition to being used more generally to help identify and remedy less immediate weaknesses in a company’s cybersecurity team.
“First, there is a big picture problem that the world is crying out for cybersecurity talent and is currently struggling to fill that gap,” Immersive Labs founder and CEO James Hadley tells me. “Secondly, the way that cyber skills are being taught is massively obsolete and puts the companies they work for at risk. On many occasions, what is taught is out of date before people leave the classroom.”
The inspiration for Immersive Labs was born out of Hadley’s experience running a summer school at GCHQ. It was while running the course that he came to the realisation that “passive classroom-based learning doesn’t suit the people, or pace, of cybersecurity.”
“Not only does the content date quickly, but the lack of challenge is just not enough for the curious and creative minds required to be good in cyber. You can’t dictate, they have to teach themselves through exploration,” he says.
“We let technical and security teams learn cyber skills like an attacker, allowing them to keep pace by combining breaking threat data with short browser-based war games. This takes the form of a series of stories that encourage people to research, analyse and build their own attacks and solutions. Whilst doing this, they learn in a fun and compelling way.”
To that end, Immersive Labs says its Series A funding will be used to grow its offering for enterprise IT and cybersecurity teams. This will include investing in headcount and infrastructure to develop the platform further, and to support the company’s go-to-market strategy. Current clients include global corporates with complex cybersecurity needs, such as BAE Systems, Sophos and Grant Thornton.
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Stripe debuts Radar anti-fraud AI tools for big businesses, says it has halted $4B in fraud to date
Cybersecurity continues to be a growing focus and problem in the digital world, and now Stripe is launching a new paid product that it hopes will help its customers better battle one of the bigger side-effects of data breaches: online payment fraud. Today, Stripe is announcing Radar for Fraud Teams, an expansion of its free AI-based Radar service that runs alongside Stripe’s core payments API to help identify and block fraudulent transactions.
And there are further efforts that Stripe is planning in coming months. Michael Manapat, Stripe’s engineering manager for Radar and machine learning, said the company is going to soon launch a private beta of a “dynamic authentication” that will bring in two-factor authentication. This is on top of Stripe’s first forays into using biometric factors in payments, made via partners like Apple and Google. With these and others, fingerprints and other physical attributes have become increasingly popular ways to identify mobile and other users.
The initial iteration of Radar launched in October 2016, and since then, Manapat tells me that it has prevented $4 billion in fraud for its “hundreds of thousands” of customers.
Considering the wider scope of how much e-commerce is affected by fraud — one study estimates $57.8 billion in e-commerce fraud across eight major verticals in a one-year period between 2016 and 2017 — this is a decent dent, but there is a lot more work to be done. And Stripe’s position of knowing four out of every five payment card numbers globally (on account of the ubiquity of its payments API) gives it a strong position to be able to tackle it.
The new paid product comes alongside an update to the core, free product that Stripe is dubbing Radar 2.0, which Stripe claims will have more advanced machine learning built into it and can therefore up its fraud detection by some 25 percent over the previous version.
New features for the whole product (free and paid) will include being able to detect when a proxy VPN is being used (which fraudsters might use to appear like they are in one country when they are actually in another) and ingesting billions of data points to train its model, which is now being updated on a daily basis automatically — itself an improvement on the slower and more manual system that Manapat said Stripe has been using for the past couple of years.
Meanwhile, the paid product is an interesting development.
At the time of the original launch, Stripe co-founder John Collison hinted that the company would be considering a paid product down the line. Stripe has said multiple times that it’s in no rush to go public — and statement that a spokesperson reiterated this week — but it’s notable that a paid tier is a sign of how Stripe is slowly building up more monetization and revenue generation.
Stripe is valued at around $9.2 billion as of its last big round in 2016. Most recently, it raised $150 million back in that November 2016 round. A $44 million from March of this year, noted in Pitchbook, was actually related to issuing stock related to its quiet acquisition of point-of-sale payments startup Index in that month — incidentally another interesting move for Stripe to expand its position and placement in the payments ecosystem. Stripe has raised around $450 million in total.
The Teams product, aimed at businesses that are big enough to have dedicated fraud detection staff, will be priced at an additional $0.02 per transaction, on top of Stripe’s basic transaction fees of a 2.9 percent commission plus 30 cents per successful card charge in the U.S. (fees vary in other markets).
The chief advantage of taking the paid product will be that teams will be able to customise how Radar works with their own transactions.
This will include a more complete set of data for teams that review transactions, and a more granular set of tools to determine where and when sales are reviewed, for example based on usage patterns or the size of the transaction. There are already a set of flags the work to note when a card is used in frequent succession across disparate geographies; but Manapat said that newer details such as analysing the speed at which payment details are entered and purchases are made will now also factor into how it flags transactions for review.
Similarly, teams will be able to determine the value at which a transaction needs to be flagged. This is the online equivalent of when certain purchases require or waive you to enter a PIN or provide a signature to seal the deal. (And it’s interesting to see that some e-commerce operations are potentially allowing some dodgy sales to happen simply to keep up the user experience for the majority of legitimate transactions.)
Users of the paid product will also be able to now use Radar to help with their overall management of how it handles fraud. This will include being able to keep lists of attributes, names and numbers that are scrutinised, and to check against them with analytics also created by Stripe to help identify trending issues, and to plan anti-fraud activities going forward.
Updated with further detail about Stripe’s funding.
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Businesses with Apple and Cisco products may now pay less for cybersecurity insurance
Apple and Cisco announced this morning a new deal with insurer Allianz that will allow businesses with their technology products to receive better terms on their cyber insurance coverage, including lower deductibles – or even no deductibles, in some cases. Allianz said it made the decision to offer these better terms after evaluating the technical foundation of Apple and… Read More
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Corelight closes $9.2M Series A to help enterprises battle ransomware
It’s already been a year of multiple high profile ransomware attacks and now cybersecurity startup Corelight has bagged a $9.2 million Series A round, led by Accel Partners. Secret Double Octopus nabs $6M for a stronger, easier alternative to regular 2FA
Israel is home to around 450 active startups in the field of cybersecurity, according to a recent report in Reuters. Now, the one with perhaps the most distinctive name of them all is announcing some funding for a novel approach to authentication. Secret Double Octopus — which borrows a concept from the world of nuclear launch codes to build extra-secure, but simple, keyless… Read More
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Microsoft Ventures backs Illusive Networks, a cybersecurity firm that protects with deception
Illusive Networks, a cybersecurity startup based out of Israel that protects networks by building “deception” frameworks to identify and trap malicious hackers, is today announcing that it has added Microsoft Ventures — the software giant’s young investment arm — as its newest strategic investor. In keeping with the its name and purpose in this world, Illusive… Read More
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