Endpoint security firm SentinelOne expects the $155 million deal to buy Scalyr will speed up its push into the lucrative XDR (Extended Detection and Response) market. [Read More]
Following a two-year downtime, an Iran-linked cyberespionage operation has recommenced with new second-stage malware and with an updated variant of the Infy malware. [Read More]
In an SEC filing, North American trucking and freight transportation logistics giant Forward Air Corporation said a December 2020 ransomware attack led to loss of revenues in the range of $7.5 million. [Read More]
The early indicators of the WannaCry attack were evident, but it spread too quickly for human security teams to react before it spread across the world like wildfire.
If the WannaCry incident taught us anything, it’s that global, widespread ransomware can and will impact organizations without any notice. The time to prepare is now.
Investigating nefarious actors online can be dangerous, as the places hunters go are likely to be full of malware and people actively monitoring for outsiders.
When implemented in series, common malware analysis environments allow security teams to handle the vast majority of threats automatically, freeing up team resources to actively hunt more advanced threats.
When implemented as part of a natively-engineered security platform, these malware identification and prevention practices can reduce the operational burden put on security teams.
Identifying malicious software by recognizing that it just damaged the system or exfiltrated some amount of information is no longer defense, but detection.
While malicious actors demanding ransoms is not new, the surge of organizations being targeted with fake extortion demands and empty threats is. Let’s look at how extortion campaigns are carried out through the “avenue of approach” lens.
Protection against the effects of ransomware starts with a clear understanding of all of the means that attackers will use to implant that first malicious package.
Attackers have developed anti-VM analysis techniques to allow the malware to recognize when it is being run on a virtual machine and fail to execute, meaning the system or threat analytics cannot make a verdict determination or extract intelligence from the sample.