Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. In enterprise security, speed is everything. The quicker an analyst can pinpoint legitimate threat signals, the faster they can identify whether there's a breach, and how to respond. As generative AI solutions like GPT develop, human analysts have the potential to supercharge their decision making. Today, cyber intelligence provider Recorded Future announced the release of what it claims is the first AI for threat intelligence.

With more than 850 employees, $200M ARR in 2021, 1,400 clients, and rapid year-over-year growth, Recorded Future is the world's most advanced intelligence platform! We are looking for an outstanding software engineer with a strong interest in data analytics to join Recorded Future's Analytics Team within the R&D organization. You will be joining a group of talented engineers, linguists and data scientists that share a common interest in solving challenging data analytics tasks in large distributed systems with rich data. The team's responsibilities include core parts of the analytics pipeline such as data harvesting, natural language processing, structured data analytics, predictive analysis, etc. We strive to make our data as actionable and comprehensive as possible and have fun.

As a Data Scientist, you will work with a team of driven, committed engineers and data scientists to take ownership of a massive, diverse dataset. Recorded Future's harvesting pipeline reads over 700,000 web sources and structured data feeds, and our real-time multilingual natural language processing technology takes that content from raw text to alerts and visualizations in minutes. You will take our data to new heights by discovering and structuring relationships between pieces of data. What you'll bring as a Data Scientist: What you'll bring as a Data Scientist: Why should you join Recorded Future? With over 600 employees, $140M ARR, 1,000 clients, and 50% year-over-year growth, Recorded Future is the world's largest privately-held security intelligence company!

Artificial intelligence and the rise of deepfake technology is something cybersecurity researchers have cautioned about for years and now it's officially arrived. Cybercriminals are increasingly sharing, developing and deploying deepfake technologies to bypass biometric security protections, and in crimes including blackmail, identity theft, social engineering-based attacks and more, experts warn. Time to get those cybersecurity defenses ready. Join Threatpost for "Fortifying Your Business Against Ransomware, DDoS & Cryptojacking Attacks" a LIVE roundtable event on Wednesday, May 12 at 2:00 PM EDT for this FREE webinar sponsored by Zoho ManageEngine. A drastic uptick in deepfake technology and service offerings across the Dark Web is the first sign a new wave of fraud is just about to crash in, according to a new report from Recorded Future, which ominously predicted that deepfakes are on the rise among threat actors with an enormous range of goals and interests.

We live in a world in which threats are constantly growing and morphing. This empowers leaders to understand what is happening, where it's happening, and why it's happening -- so they can take decisive action to protect citizens. Advancements in artificial intelligence (AI) are driving unprecedented change and opportunity in this space. The ability to merge physical models with digital content and conduct analysis at extraordinary speed is a game-changer for the GEOINT workforce -- but such a major industry shakeup also presents new challenges. A new study by the United States Geospatial Intelligence Foundation (USGIF) and MeriTalk, "Mapping AI to the GEOINT Workforce," shows that 91% of geospatial intelligence stakeholders believe AI has the potential to greatly improve the discipline -- particularly in the areas of national security, emergency response, and urban planning and development.

A big challenge in collecting and analyzing intelligence has always been scalability. Good, actionable intelligence takes expertise to develop. Let's say you're a government trying to gather information on a foreign power. You'll need experts who speak the language, know the culture well enough to blend in, have the right skill sets, and are sympathetic to your goals. Finding enough experts who meet those criteria will be difficult -- and even then, it still might not be enough to get regular, actionable intelligence.

While tracking criminal activity on dark web marketplaces, a threat intelligence team Insikt Group of the security research firm Recorded Future discovered a hacker selling classified military documents for a meager amount of $150-200 on the Deep Web and Dark Web forum. According to the research team, the hacker got a hold on the documents after they intruded by exploiting an FTP vulnerability in Netgear routers that's been known for two years. Once the hacker got an access to the router, the intruder was easily able to invade into a captain's personal computer and steal a cache of sensitive documents. "While such course books are not classified materials on their own," Recorded Future said, "in unfriendly hands, they could provide an adversary the ability to assess technical capabilities and weaknesses in one of the most technologically advanced aircrafts." The documents include contained sensitive materials, like "the M1 Abrams maintenance manual, a tank platoon training course, a crew survival course, and documentation on improvised explosive device (IED) mitigation tactics."

The hacker sought buyers for maintenance documents about the MQ-9 Reaper drone, a remotely controlled aerial vehicle used by the Pentagon and other parts of the government to conduct offensive strikes or reconnaissance and surveillance operations. Discovery of the attempted sale of the stolen documents comes amid heightened concern about how U.S. military secrets may be insufficiently protected from hackers. Military officials said last month that the Defense Department's inspector general was investigating a major security breach after Chinese hackers allegedly stole data pertaining to submarine warfare, including plans to build a supersonic antiship missile. There was no evidence that the hacker who acquired the Reaper drone documents was affiliated with a foreign country, or that he was intentionally seeking to obtain military documents, said Andrei Barysevich, a senior threat researcher at Recorded Future, the U.S.-based cybersecurity firm that spotted the attempted sale. Instead, the hacker scanned large parts of the internet for misconfigured Netgear routers and exploited a two-year-old known vulnerability, involving default login credentials, to steal files from compromised machines.

Manuals on Reaper drones and details on how to defeat improvised explosive devices were leaked and it appears military personnel were hacked, according to cybersecurity researchers. The dark web drug trade might have depleted in recent months, but all manner of other black market trades continue to thrive in the underbelly of the internet. On Wednesday, researchers at cybercrime tracker Recorded Future reported that a hacker was trying to flog documents about the Reaper drone used across federal government agencies for between $150 and $200. It appeared they'd successfully hacked into at least two computers belonging to U.S. military personnel and the theft could have a significant impact on American campaigns abroad, Recorded Future warned. The company spoke directly with the hacker, learning the documents had been obtained by using a previously-disclosed vulnerability in Netgear routers.

If you've walked around any security conferences recently, you'll have heard dozens of vendors talking about artificial intelligence (AI) and machine learning. But what do they actually do? Are they really going to usher in a grand age of cybersecurity? And are security analysts about to be collectively out of a job? Recently, Recorded Future co-hosted a webinar with SANS Institute with the goal of helping security conscious organizations understand how machine learning can help them process an almost infinite number of inputs into a small number of actionable outputs.