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Threat Finds
Attacchi informatici ispirati all'afnio neutralizzati dall'IA






On March 11 and 12, 2021, Darktrace detected multiple attempts by a broad campaign to attack vulnerable servers in customer environments. The campaign targeted Internet-facing Microsoft Exchange servers, exploiting the recently discovered ProxyLogon vulnerability (CVE-2021-26855).
While this exploit was initially attributed to a group known as Hafnium, Microsoft has announced that the vulnerability is also being rapidly weaponized by other threat actors. These new, unattributed campaigns, which have never been seen before, have been disrupted by Cyber AI in real time.
Hafnium copycats
As soon as a vulnerability is made public it is common for there to be an influx of attacks as hackers capitalize on the chaos and attempt to compromise vulnerable networks.
Patches are rapidly reverse-engineered by hackers once they have been published by the vendor, leading to mass high-impact exploits. At the same time, the offensive tooling trickles down from the first adopters, such as nation-state actors, to ransomware gangs and other opportunistic attackers. Darktrace has observed this exact phenomenon as a result of Hafnium’s attacks against vulnerable Microsoft Exchange email servers this month.
Exchange servers attacked: AI analysis
Cyber AI has observed threat actors attempting to download and install malware using ProxyLogon as the initial attack vector. For customers with Autonomous Response, the malicious payload was intercepted at this point, stopping the attack before any developments.
In other Darktrace customer environments, the Darktrace Immune System identified and alerted on every stage of the attack. Generally, the malware has been observed acting as a generic backdoor, without much follow-up activity. Various forms of command and control (C2) channels were detected, including Telegra[.]ph. In a few intrusions, the attackers installed cryptocurrency miners.
Once a foothold has been established in the digital environment, it is likely that the actors will begin a hands-on-keyboard attack, exfiltrating data, moving laterally, or deploying ransomware.

Figure 1: Timeline of a typical ProxyLogon exploit
After the ProxyLogon vulnerability was exploited, the Exchange servers reached out to the malicious domain microsoftsoftwaredownload[.]com, utilizing a PowerShell User Agent. Darktrace flagged this anomalous behavior as the particular User Agent had never been used before by the Exchange server, let alone to access a malicious domain which had never been observed in the network.

Figure 2: Darktrace revealing an anomalous PowerShell connection
The malware executable was masqueraded as a ZIP file, further trying to obfuscate the attack. Darktrace identified this highly anomalous file download and the masqueraded file.

Figure 3: Darktrace revealing key information around the anomalous file download
In some cases, Darktrace AI also observed cryptocurrency mining seconds or minutes after the initial malware download.

Figure 4: Darktrace’s Crypto Currency Mining model is breached
In terms of C2 traffic, Darktrace has observed various potential channels. Around the time of the malware download, some of the Exchange servers began to beacon out to several external destinations using unusual SSL or TLS encrypted connections.
- Telegra[.]ph — popular messenger application
- dev.opendrive[.]com — cloud storage service
- od[.]lk — cloud storage service
In this case, Darktrace recognized that none of these three external domains had ever been contacted before by anybody in the organization, let alone in a beaconing fashion. The fact that these communications started around the same time as the malware downloads strongly suggests a correlation. Darktrace’s Cyber AI Analyst automatically began an investigation into the incident, stitching together these events into one coherent narrative.
Investigating with AI
Cyber AI Analyst then automatically created a summary incident report about the activity, covering the malware download as well as the various C2 channels observed.

Figure 5: Cyber AI Analyst automatically generating a high-level incident summary
Looking at an infected Exchange server ([REDACTED].local) from a birds-eye perspective shows that Darktrace created various alerts when the attack hit. Every one of the colored dots in the graph below represents a major anomaly detected by Darktrace.

Figure 6: Darktrace reveals the anomalous number of connections and subsequent model breaches
This activity was prioritized as the most urgent incident in Cyber AI Analyst among a full week’s worth of data. In this particular organization, there were only four incidents for that week in total in Cyber AI Analyst. Such precise and clear alerting allows security teams to immediately understand the top threats facing their digital environment, without being overwhelmed by unnecessary alerts and false positives.
Machine-speed response
For customers with Darktrace Antigena, Antigena autonomously acted to block all outgoing traffic to malicious external endpoints on the relevant ports. This behavior is held for several hours to interrupt the threat actor from escalating the attack, while giving security teams time to react and remediate.
Antigena responded within seconds of the attack starting, effectively containing the attack in its earliest stage – without interrupting regular business activity (emails could still be sent and received), and despite this being a zero-day campaign.

Figure 7: Darktrace Antigena autonomously responds
Catching a zero-day exploit
This is not the first time Darktrace has stopped an attack leveraging a zero-day or a freshly released n-day vulnerability. Back in March 2020, Darktrace detected APT41 exploiting the Zoho ManageEngine vulnerability, two weeks before public attribution.
It is highly likely that there will be more cyber-criminals exploiting ProxyLogon in the wake of Hafnium. And while the recent Exchange server vulnerabilities were today’s threat, next time it might be a software or hardware supply chain attack, or a different zero-day. Novel threats are emerging every week. In this climate we now find ourselves in, where ‘known unknowns’ which are difficult or impossible to pre-define are the new norm, we need to be more adaptable and proactive than ever.
As soon as an attacker begins to exhibit unusual activity, Darktrace AI will detect it, even if there is no threat intelligence associated with the attack. This is where Darktrace works best, autonomously detecting, investigating and responding to advanced and never-before-seen threats in real time.
Learn more about the Darktrace Immune System
Example Darktrace model detections:
- Antigena / Network / Compliance / Antigena Crypto Currency Mining Block
- Compliance / Crypto Currency Mining Activity
- Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
- Anomalous Connection / Suspicious Expired SSL
- Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
- Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block
- Device / Initial Breach Chain Compromise
- Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
- Anomalous File / Masqueraded File Transfer
- Anomalous File / EXE from Rare External Location
- Antigena / Network / External Threat / Antigena Suspicious File Block
- Antigena / Network / External Threat / Antigena File then New Outbound Block
- Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach
- Anomalous File / Internet Facing System File Download
- Device / New PowerShell User Agent
- Anomalous File / Multiple EXE from Rare External Locations
- Anomalous Connection / Powershell to Rare External
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Inside the SOC
Black Basta: Old Dogs with New Tricks



What is Black Basta?
Over the past year, security researchers have been tracking a new ransomware group, known as Black Basta, that has been observed targeted organizations worldwide to deploy double extortion ransomware attacks since early 2022. While the strain and group are purportedly new, evidence seen suggests they are an offshoot of the Conti ransomware group [1].
The group behind Black Basta run a Ransomware as a Service (RaaS) model. They work with initial access brokers who will typically already have a foothold in company infrastructure to begin their attacks. Once inside a network, they then pivot internally using numerous tools to further their attack.
Black Basta Ransomware
Like many other ransomware actors, Black Basta uses double extortion as part of its modus operandi, exfiltrating sensitive company data and using the publication of this as a second threat to affected companies. This is also advertised on a dark web site, setup by the group to apply further pressure for affected companies to make ransom payments and avoid reputational damage.
The group also seems to regularly take advantage of existing tools to undertake the earlier stages of their attacks. Notably, the Qakbot banking trojan, seems to be the malware often used to gain an initial foothold within compromised environments.
Analysis of the tools, procedures and infrastructure used by Black Basta belies a maturity to the actors behind the ransomware. Their models and practices suggest those involved are experienced individuals, and security researchers have drawn possible links to the Conti ransomware group.
As such, Black Basta is a particular concern for security teams as attacks will likely be more sophisticated, with attackers more patient and able to lie low on digital estates for longer, waiting for the opportune moment to strike.
Cyber security is an infinite game where defender and attacker are stuck as cat and mouse; as new attacks evolve, security vendors and teams respond to the new indicators of compromise (IoCs), and update their existing rulesets and lists. As a result, attackers are forced to change their stripes to evade detection or sometimes even readjust their targets and end goals.
Anomaly Based Detection
By using the power of Darktrace’s Self-Learning AI, security teams are able to detect deviations in behavior. Threat actors need to move through the kill chain to achieve their aims, and in doing so will cause affected devices within networks to deviate from their expected pattern of life. Darktrace’s anomaly-based approach to threat detection allows it recognize these subtle deviations that indicate the presence of an attacker, and stop them in their tracks.
Additionally, the ecosystem of cyber criminals has matured in the last few decades. It is well documented how many groups now operate akin to legitimate companies, with structure, departments and governance. As such, while new attack methods and tactics do appear in the wild, the maturity in their business models belie the experience of those behind the attack.
As attackers grow their business models and develop their arsenal of attack vectors, it becomes even more critical for security teams to remain vigilant to anomalies within networks, and remain agnostic to underlying IoCs and instead adopt anomaly detection tools able to identify tactics, techniques, and procedures (TTPs) that indicate attackers may be moving through a network, ahead of deployment of ransomware and data encryption.
Darktrace’s Coverage of Black Basta
In April 2023, the Darktrace Security Operations Center (SOC) assisted a customer in triaging and responding to an ongoing ransomware infection on their network. On a Saturday, the customer reached out directly to the Darktrace analyst team via the Ask the Expert service for support after they observed encrypted files and locked administrative accounts on their network. The analyst team were able to investigate and clarify the attack path, identifying affected devices and assisting the customer with their remediation. Darktrace DETECT™ observed varying IoCs and TTPs throughout the course of this attack’s kill chain; subsequent analysis into these indicators revealed this had likely been a case of Black Basta seen in the wild.
Intrusione iniziale
The methods used by the group to gain an initial foothold in environments varies – sometimes using phishing, sometimes gaining access through a common vulnerability exposed to the internet. Black Basta actors appear to target specific organizations, as opposed to some groups who aim to hit multiple at once in a more opportunistic fashion.
In the case of the Darktrace customer likely affected by Black Basta, it is probable that the initial intrusion was out of scope. It may be that the path was via a phishing email containing an Microsoft Excel spreadsheet that launches malicious powershell commands; a noted technique for Black Basta. [3][4] Alternatively, the group may have worked with access brokers who already had a foothold within the customer’s network.
One particular device on the network was observed acting anomalously and was possibly the first to be infected. The device attempted to connect to multiple internal devices over SMB, and connected to a server that was later found to be compromised and is described throughout the course of this blog. During this connection, it wrote a file over SMB, “syncro.exe”, which is possibly a legitimate Remote Management software but could in theory be used to spread an infection laterally. Use of this tool otherwise appears sporadic for the network, and was notably unusual for the environment.
Given these timings, it is possible this activity is related to the likely Black Basta compromise. However, there is some evidence online that use of Syncro has been seen installed as part of the execution of loaders such as Batloader, potentially indicating a separate or concurrent attack [5].
Internal Reconnaissance + Lateral Movement
However the attackers gained access in this instance, the first suspicious activity observed by Darktrace originated from an infected server. The attacker used their foothold in the device to perform internal reconnaissance, enumerating large portions of the network. Darktrace DETECT’s anomaly detection noted a distinct rise in connections to a large number of subnets, particularly to closed ports associated with native Windows services, including:
- 135 (RPC)
- 139 (NetBIOS)
- 445 (SMB)
- 3389 (RDP)
During the enumeration, SMB connections were observed during which suspiciously named executable files were written:
- delete.me
- covet.me
Data Staging and Exfiltration
Around 4 hours after the scanning activity, the attackers used their knowledge gained during enumeration about the environment to begin gathering and staging data for their double extortion attempts. Darktrace observed the same infected server connecting to a file storage server, and downloading over 300 GiB of data. Darktrace DETECT identified that the connections had been made via SMB and was able to present a list of filenames to the customer, allowing their security team to determine the data that had likely been exposed to the attackers.
The SMB paths detected by Darktrace showed a range of departments’ file areas being accessed by threat actors. This suggests they were interested in getting as much varied data as possible, presumably in an attempt to ensure a large amount of valuable information was at their disposal to make any threats of releasing them more credible, and more damaging to the company.
Shortly after the download, the device made an external connection over SSH to a rare domain, dataspt[.]com, hosted in the United States. The connection itself was made over an unusual port, 2022, and Darktrace recognized that the domain was new for the network.
During this upload, the threat actors uploaded a similar volume of data to the 300GiB that had been downloaded internally earlier. Darktrace flagged the usual elements of this external upload, making the identification and triage of this exfiltration attempt easier for the customer.
On top of this, Darktrace’s autonomous investigation tool Cyber AI Analyst™ launched an investigation into this on-going activity and was able to link the external upload events to the internal download, identifying them as one exfiltration incident rather than two isolated events. AI Analyst then provided a detailed summary of the activity detected, further speeding up the identification of affected files.
Preparing for Exploitation
All the activity documented so far had occurred on a Wednesday evening. It was at this point that the burst of activity calmed, and the ransomware lay in wait within the environment. Other devices around the network, particularly those connected to by the original infected server and a domain controller, were observed performing some elements of anomalous activity, but the attack seemed to largely take a pause.
However, on the Saturday morning, 3 days later, the compromised server began to change the way it communicated with attackers by reaching out to a new command and control (C2) endpoint. It seemed that attackers were gearing up for their attack, taking advantage of the weekend to strike while security teams often run with a reduced staffing.
Darktrace identified connections to a new endpoint within 4 minutes of it first being seen on the customer’s environment. The server had begun making repeated SSL connections to the new external endpoint, faceappinc[.]com, which has been flagged as malicious by various open-source intelligence (OSINT) sources.
The observed JA3 hash (d0ec4b50a944b182fc10ff51f883ccf7) suggests that the command-line tool BITS Admin was being used to launch these connections, another suggestion of the use of mature tooling.
In addition to this, Darktrace also detected the server using an administrative credential it had never previously been associated with. Darktrace recognized that the use of this credential represented a deviation from the device’s usual activity and thus could be indicative of compromise.
The server then proceeded to use the new credential to authenticate over Keberos before writing a malicious file (“management.exe”) to the Temp directory on a number of internal devices.
Encryption
At this point, the number of anomalous activities detected from the server increased massively as the attacker seems to connect networkwide in an attempt to cause as quick and destructive an encryption effort as possible. Darktrace observed numerous files that had been encrypted by a local process. The compromised server began to write ransom notes, named “instructions_read_me.txt” to other file servers, which presumably also had successfully deployed payloads. While Black Basta actors had initially been observed dropping ransom notes named “readme.txt”, security researchers have since observed and reported an updated variant of the ransomware that drops “instructions_read_me_.txt”, the name of the file detected by Darktrace, instead [6].
Another server was also observed making repeated SSL connections to the same rare external endpoint, faceappinc[.]com. Shortly after beginning these connections, the device made an HTTP connection to a rare IP address with no hostname, 212.118.55[.]211. During this connection, the device also downloaded a suspicious executable file, cal[.]linux. OSINT research linked the hash of this file to a Black Basta Executable and Linkable File (ELF) variant, indicating that the group was highly likely behind this ransomware attack.
Of particular interest again, is how the attacker lives off the land, utilizing pre-installed Windows services. Darktrace flagged that the server was observed using PsExec, a remote management executable, on multiple devices.
Darktrace Assistance
Darktrace DETECT was able to clearly detect and provide visibility over all stages of the ransomware attack, alerting the customer with multiple model breaches and AI Analyst investigation(s) and highlighting suspicious activity throughout the course of the attack.
For example, the exfiltration of sensitive data was flagged for a number of anomalous features of the meta-data: volume; rarity of the endpoint; port and protocol used.
In total, the portion of the attack observed by Darktrace lasted about 4 days from the first model breach until the ransomware was deployed. In particular, the encryption itself was initiated on a Saturday.
The encryption event itself was initiated on a Saturday, which is not uncommon as threat actors tend to launch their destructive attacks when they expect security teams will be at their lowest capacity. The Darktrace SOC team regularly observes and assists in customer’s in the face of ransomware actors who patiently lie in wait. Attackers often choose to strike as security teams run on reduced hours of manpower, sometimes even choosing to deploy ahead of longer breaks for national or public holidays, for example.
In this case, the customer contacted Darktrace directly through the Ask the Expert (ATE) service. ATE offers customers around the clock access to Darktrace’s team of expert analysts. Customers who subscribe to ATE are able to send queries directly to the analyst team if they are in need of assistance in the face of suspicious network activity or emerging attacks.
In this example, Darktrace’s team of expert analysts worked in tandem with Cyber AI Analyst to investigate the ongoing compromise, ensuring that the investigation and response process were completed as quickly and efficiently as possible.
Thanks to Darktrace’s Self-Learning AI, the analyst team were able to quickly produce a detailed report enumerating the timeline of events. By combining the human expertise of the analyst team and the machine learning capabilities of AI Analyst, Darktrace was able to quickly identify anomalous activity being performed and the affected devices. AI Analyst was then able to collate and present this information into a comprehensive and digestible report for the customer to consult.
Conclusion
It is likely that this ransomware attack was undertaken by the Black Basta group, or at least using tools related to their method. Although Black Basta itself is a relatively novel ransomware strain, there is a maturity and sophistication to its tactics. This indicates that this new group are actually experienced threat actors, with evidence pointing towards it being an offshoot of Conti.
The Pyramid of Pain is a well trodden model in cyber security, but it can help us understand the various features of an attack. Indicators like static C2 destinations or file hashes can easily be changed, but it’s the underlying TTPs that remain the same between attacks.
In this case, the attackers used living off the land techniques, making use of tools such as BITSAdmin, as well as using tried and tested malware such as Qakbot. While the domains and IPs involved will change, the way these malware interact and move about systems remains the same. Their fingerprint therefore causes very similar anomalies in network traffic, and this is where the strength of Darktrace lies.
Darktrace’s anomaly-based approach to threat detection means that these new attack types are quickly drawn out of the noise of everyday traffic within an environment. Once attackers have gained a foothold in a network, they will have to cause deviation from the usual pattern of a life on a network to proceed; Darktrace is uniquely placed to detect even the most subtle changes in a device’s behavior that could be indicative of an emerging threat.
Machine learning can act as a force multiplier for security teams. Working hand in hand with the Darktrace SOC, the customer was able to generate cohesive and comprehensive reporting on the attack path within days. This would be a feat for humans alone, requiring significant resources and time, but with the power of Darktrace’s Self-Learning AI, these deep and complex analyses become as easy as the click of a button.
Credit to: Matthew John, Director of Operations, SOC, Paul Jennings, Principal Analyst Consultant
Appendices
Darktrace DETECT Model Breaches
Internal Reconnaissance
Device / Multiple Lateral Movement Model Breaches
Device / Large Number of Model Breaches
Device / Network Scan
Device / Anomalous RDP Followed by Multiple Model Breaches
Device / Possible SMB/NTLM Reconnaissance
Device / SMB Lateral Movement
Anomalous Connection / SMB Enumeration
Anomalous Connection / Possible Share Enumeration Activity
Device / Suspicious SMB Scanning Activity
Device / RDP Scan
Anomalous Connection / Active Remote Desktop Tunnel
Device / Increase in New RPC Services
Device / ICMP Address Scan
Download and Upload
Unusual Activity / Enhanced Unusual External Data Transfer
Unusual Activity / Unusual External Data Transfer
Anomalous Connection / Uncommon 1 GiB Outbound
Anomalous Connection / Data Sent to Rare Domain
Anomalous Connection / Download and Upload
Compliance / SSH to Rare External Destination
Anomalous Server Activity / Rare External from Server
Anomalous Server Activity / Outgoing from Server
Anomalous Connection / Application Protocol on Uncommon Port
Anomalous Connection / Multiple Connections to New External TCP Port
Device / Anomalous SMB Followed By Multiple Model Breaches
Unusual Activity / SMB Access Failures
Lateral Movement and Encryption
User / New Admin Credentials on Server
Compliance / SMB Drive Write
Device / Anomalous RDP Followed By Multiple Model Breaches
Anomalous Connection / High Volume of New or Uncommon Service Control
Anomalous Connection / New or Uncommon Service Control
Device / New or Unusual Remote Command Execution
Anomalous Connection / SMB Enumeration
Additional Beaconing and Tooling
Device / Initial Breach Chain Compromise
Device / Multiple C2 Model Breaches
Compromise / Large Number of Suspicious Failed Connections
Compromise / Sustained SSL or HTTP Increase
Compromise / SSL or HTTP Beacon
Compromise / Suspicious Beaconing Behavior
Compromise / Large Number of Suspicious Successful Connections
Compromise / High Volume of Connections with Beacon Score
Compromise / Slow Beaconing Activity To External Rare
Compromise / SSL Beaconing to Rare Destination
Compromise / Beaconing Activity To External Rare
Compromise / Beacon to Young Endpoint
Compromise / Agent Beacon to New Endpoint
Anomalous Server Activity / Rare External from Server
Anomalous Connection / Multiple Failed Connections to Rare Endpoint
Anomalous File / EXE from Rare External Location
IoC - Type - Description + Confidence
dataspt[.]com - Hostname - Highly Likely Exfiltration Server
46.22.211[.]151:2022 - IP Address and Unusual Port - Highly Likely Exfiltration Server
faceappinc[.]com - Hostname - Likely C2 Infrastructure
Instructions_read_me.txt - Filename - Almost Certain Ransom Note
212.118.55[.]211 - IP Address - Likely C2 Infrastructure
delete[.]me - Filename - Potential lateral movement script
covet[.]me - Filename - Potential lateral movement script
d0ec4b50a944b182fc10ff51f883ccf7 - JA3 Client Fingerprint - Potential Windows BITS C2 Process
/download/cal.linux - URI - Likely BlackBasta executable file
1f4dcfa562f218fcd793c1c384c3006e460213a8 - Sha1 File Hash - Likely BlackBasta executable file

References
[1] https://blogs.blackberry.com/en/2022/05/black-basta-rebrand-of-conti-or-something-new
[2] https://www.cybereason.com/blog/threat-alert-aggressive-qakbot-campaign-and-the-black-basta-ransomware-group-targeting-u.s.-companies
[4] https://unit42.paloaltonetworks.com/atoms/blackbasta-ransomware/
[6] https://www.pcrisk.com/removal-guides/23666-black-basta-ransomware
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Using AI to Help Humans Function Better During a Cyber Crisis



Within cyber security, crises are a regular occurrence. Whether due to the ever-changing tactics of threat actors or the emergence of new vulnerabilities, security teams find themselves under significant pressure and frequently find themselves in what psychologists term "crisis states."1
A crisis state refers to an internal state marked by confusion and anxiety to such an extent that previously effective coping mechanisms give way to ineffective decision-making and behaviors.2
Given the prevalence of crises in the field of cyber security, practitioners are more prone to consistently making illogical choices due to the intense pressure they experience. They also grapple with a constant influx of rapidly changing information, the need for swift decision-making, and the severe consequences of errors in judgment. They are often asked to assess hundreds of variables and uncertain factors.
The frequency of crisis states is expected to rise as generative AI empowers cyber criminals to accelerate the speed, scale, and sophistication of their attacks.
Why is it so challenging to operate effectively and efficiently during a crisis state? Several factors come into play.
Firstly, individuals are inclined to rely on their instincts, rendering them susceptible to cognitive biases. This makes it increasingly difficult to assimilate new information, process it appropriately, and arrive at logical decisions. Since crises strike unexpectedly and escalate rapidly into new unknowns, responders experience heightened stress, doubt and insecurity when deciding on a course of action.
These cognitive biases manifest in various forms. For instance, confirmation bias prompts people to seek out information that aligns with their pre-existing beliefs, while hindsight bias makes past events seem more predictable in light of present context and information.
Crises also have a profound impact on information processing and decision-making. People tend to simplify new information and often cling to the initial information they receive rather than opting for the most rational decision.
For instance, if an organization has successfully thwarted a ransomware attack in the past, a defender might assume that employing the same countermeasures will suffice for a subsequent attack. However, ransomware tactics are constantly evolving, and a subsequent attack could employ different strategies that evade the previous defenses. In a crisis state, individuals may revert to their prior strategy instead of adapting based on the latest information.
Given there are deeply embedded psychological tendencies and hard-wired decision-making processes leading to a reduction in logic during a crisis, humans need support from technology that does not suffer from the same limitations, particularly in the post-incident phase, where stress levels go into overdrive.
In the era of rapidly evolving novel attacks, security teams require a different approach: AI.
AI can serve as a valuable tool to augment human decision-making, from detection to incident response and mitigation. This is precisely why Darktrace introduced HEAL, which leverages self-learning AI to assist teams in increasing their cyber resilience and managing live incidents, helping to alleviate the cognitive burden they face.
Darktrace HEAL™ learns from your environment, including data points from real incidents and generates simulations to identify the most effective approach for remediation and restoring normal operations. This reduces the overwhelming influx of information and facilitates more effective decision-making during critical moments.
Furthermore, HEAL offers security teams the opportunity to safely simulate realistic attacks within their own environment. Using specific data points from the native environment, simulated incidents prepare security teams for a variety of circumstances which can be reviewed on a regular basis to encourage effective habit forming and reduce cognitive biases from a one-size-fits-all approach. This allows them to anticipate how attacks might unfold and better prepare themselves psychologically for potential real-world incidents.
With the right models and data, AI can significantly mitigate human bias by providing remediation recommendations grounded in evidence and providing proportionate responses based on empirical evidence rather than personal interpretations or instincts. It can act as a guiding light through the chaos of an attack, providing essential support to human security teams.
1 www.cybersecuritydive.com/news/incident-response-impacts-wellbeing/633593
2 blog.bcm-institute.org/crisis-management/making-decision-during-a-crisis