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Utilizing AI Security Against Phishing Campaigns

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26
Sep 2023
26
Sep 2023
Learn how Darktrace leveraged generative AI tools to detect and combat phishing email campaigns. Discover how AI is reshaping cybersecurity strategies.

Stopping the bad while allowing the good

Since its inception, email has been regarded as one of the most important tools for businesses, revolutionizing communication and allowing global teams to become even more connected. But besides organizations heavily relying on email for their daily operations, threat actors have also recognized that the inbox is one of the easiest ways to establish an initial foothold on the network.

Today, not only are phishing campaigns and social engineering attacks becoming more prevalent, but the level of sophistication of these attacks are also increasing with the help of generative AI tools that allow for the creation of hyper-realistic emails with minimal errors, effectively lowering the barrier to entry for threat actors. These diverse and stealthy types of attacks evade traditional email security tools based on rules and signatures, because they are less likely to contain the low-sophistication markers of a typical phishing attack.  

In a situation where the sky is the limit for attackers and security teams are lean, how can teams equip themselves to tackle these threats? How can they accurately detect increasingly realistic malicious emails and neutralize these threats before it is too late? And importantly, how can email security block these threats while allowing legitimate emails to flow freely?

Instead of relying on past attack data, Darktrace’s Self-Learning AI detects the slightest deviation from a user’s pattern of life and responds autonomously to contain potential threats, stopping novel attacks in their tracks before damage is caused. It doesn’t define ‘good’ and ‘bad’ like traditional email tools, rather it understands each user and what is normal for them – and what’s not.

This blog outlines how Darktrace/Email™ used its understanding of ‘normal’ to accurately detect and respond to a sustained phishing campaign targeting a real-life company.

Responding to a sustained phishing attack

Over the course of 24 hours, Darktrace detected multiple emails containing different subjects, all from different senders to different recipients in one organization. These emails were sent from different IP addresses, but all came from the same autonomous system number (ASN).

Figure 1: The sender freemail addresses and subject lines all followed a certain format. The subject lines followed the format of “<First name> <Last name>”, possibly to induce curiosity. The senders were all freemail accounts and contained first names, last names and some numbers, showing the attempts to make these email addresses appear legitimate.

The emails themselves had many suspicious indicators. All senders had no prior association with the recipient, and the emails generated a high general inducement score. This score is generated by structural and non-specific content analysis of the email – a high score indicates that the email is trying to induce the recipient into taking a particular action, which may lead to account compromise.

Additionally, each email contained a visually prominent link to a file storage service, hidden behind a shortened bit.ly link. The similarities across all these emails pointed to a sustained campaign targeting the organization by a single threat actor.

Figure 2: One of the emails is shown above. Like all the other emails, it contained a highly suspicious and shortened link.
Figure 3: In another one of the emails, the link observed had similar characteristics. But this email stands out from the rest. The sender's name seems to be randomly set – the 3 alphabets are close to each other on the keyboard.

With all these suspicious indicators, many models were breached. This drove up the anomaly score, causing Darktrace/Email to hold all suspicious emails from the recipients’ inboxes, safeguarding the recipients from potential account compromise and disallowing the threats from taking hold in the network.

Imagining a phishing attack without Darktrace/Email

So what could have happened if Darktrace had not withheld these emails, and the recipients had clicked on the links? File storage sites have a wide variety of uses that allow attackers to be creative in their attack strategy. If the user had clicked on the shortened link, the possible consequences are numerous. The link could have led to a login page for unsuspecting victims to input their credentials, or it could have hosted malware that would automatically download if the link was clicked. With the compromised credentials, threat actors could even bypass MFA, change email rules, or gain privileged access to a network. The downloaded malware might also be a keylogger, leading to cryptojacking, or could open a back door for threat actors to return to at a later time.

Figure 4: Darktrace/Email highlights suspicious link characteristics and provides an option to preview the pages.
Figure 5: At the point of writing, both links could not be reached. This could be because they were one-time unique links created specifically for the user, and can no longer be accessed once the campaign has ceased.

The limits of traditional email security tools

Secure email gateways (SEGs) and static AI security tools may have found it challenging to detect this phishing campaign as malicious. While Darktrace was able to correlate these emails to determine that a sustained phishing campaign was taking place, the pattern among these emails is far too generic for specific rules as set in traditional security tools. If we take the characteristic of the freemail account sender as an example, setting a rule to block all emails from freemail accounts may lead to more legitimate emails being withheld, since these addresses have a variety of uses.

With these factors in mind, these emails could have easily slipped through traditional security filters and led to a devastating impact on the organization.

Conclusion

As threat actors step up their attacks in sophistication, prioritizing email security is more crucial than ever to preserving a safe digital environment. In response to these challenges, Darktrace/Email offers a set-and-forget solution that continuously learns and adapts to changes in the organization.  

Through an evolving understanding of every environment in which it is deployed, its threat response becomes increasingly precise in neutralizing only the bad, while allowing the good – delivering email security that doesn’t come at the expense of business growth.

INSIDE THE SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
AUTHOR
ABOUT ThE AUTHOR
Germaine Tan
VP of Cyber Risk Management

Germaine is the Director of Analysis, APAC at Darktrace. Based in Singapore, she works with CISOs, managers and security teams all over APAC on model optimization and operationalization of Darktrace in their digital environments. She also manages the team of 17 analysts in the APAC region that threat hunts and monitors networks from all over the world. Germaine holds a Bachelor of Science in Engineering and a Masters of Science in Technology Management from Nanyang Technological University. She is CISSP, CRISC and CEH certified.

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What you need to know about the new SEC Cybersecurity rules

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17
Jul 2024

What is new in 2023 to SEC cybersecurity rules?

Form 8-K Item 1.05: Requiring the timely disclosure of material cybersecurity incidents.

Regulation S-K item 106: requiring registrants’ annual reports on Form 10-K to address cybersecurity risk management, strategy, and governance processes.

Comparable disclosures are required for reporting foreign private issuers on Forms 6-K and 20-F respectively.

What is Form 8-K Item 1.05 SEC cybersecurity rules?

Form 8-K Item 1.05 requires the following to be reported within four business days from when an incident is determined to be “material” (1), unless extensions are granted by the SEC under certain qualifying conditions:

“If the registrant experiences a cybersecurity incident that is determined by the registrant to be material, describe the material aspects of the nature, scope, and timing of the incident, and the material impact or reasonably likely material impact on the registrant, including its financial condition and results of operations.” (2, 3)

How does the SEC define cybersecurity incident?

Cybersecurity incident defined by the SEC means an unauthorized occurrence, or a series of related unauthorized occurrences, on or conducted through a registrant’s information systems that jeopardizes the confidentiality, integrity, or availability of a registrant’s information systems or any information residing therein. (4)

How can Darktrace assist in the process of disclosing incidents to the SEC?

Accelerate reporting

Darktrace’s Cyber AI Analyst generates automated reports that synthesize discrete data points potentially indicative of cybersecurity threats, forming reports that provide an overview of the evolution and impact of a threat.

Thus, when a potential threat is identified by Darktrace, AI Analyst can quickly compile information that organizations might include in their disclosure of an occurrence they determined to be material, including the following: incident timelines, incident events, incident summary, related model breaches, investigation process (i.e., how Darktrace’s AI conducted the investigation), linked incident events, and incident details. The figure below illustrates how Darktrace compiles and presents incident information and insights in the UI.

Overview of information provided in an ‘AI Analyst Report’ that could be relevant to registrants reporting a material cybersecurity incident to the SEC
Figure 1: Overview of information provided in an ‘AI Analyst Report’ that could be relevant to registrants reporting a material cybersecurity incident to the SEC

It should be noted that Instruction 4 to the new Form 8-K Item 1.05 specifies the “registrant need not disclose specific or technical information about its planned response to the incident or its cybersecurity systems, related networks and devices, or potential system vulnerabilities in such detail as would impede the registrant’s response or remediation of the incident” (5).

As such, the incident report generated by Darktrace may provide more information, including technical details, than is needed for the 8-K disclosure. In general, users should take appropriate measures to ensure that the information they provide in SEC reports meets the requirements outlined by the relevant regulations. Darktrace cannot recommend that an incident should be reported, nor report an incident itself.

Determine if a cybersecurity incident is material

Item 1.05 requires registrants to determine for themselves whether cybersecurity incidents qualify as ‘material’. This involves considerations such as ‘the nature scope and timing of the incident, and the material impact or reasonably likely material impact on the registrant, including its financial condition and results of operations.’

While it is up to the registrant to determine, consistent with existing legal standards, the materiality of an incident, Darktrace’s solution can provide relevant information which might aid in this evaluation. Darktrace’s Threat Visualizer user interface provides a 3-D visualization of an organization’s digital environment, allowing users to assess the likely degree to which an attack may have spread throughout their digital environment. Darktrace Cyber AI Analyst identifies connections among discrete occurrences of threatening activity, which can help registrants quickly assess the ‘scope and timing of an incident'.

Furthermore, in order to establish materiality it would be useful to understand how an attack might extend across recipients and environments. In the image below, Darktrace/Email identifies how a user was impacted across different platforms. In this example, Darktrace/Email identified an attacker that deployed a dual channel social engineering attack via both email and a SaaS platform in an effort to acquire login credentials. In this case, the attacker useding a legitimate SharePoint link that only reveals itself to be malicious upon click. Once the attacker gained the credentials, it proceeded to change email rules to obfuscate its activity.

Darktrace/Email presents this information in one location, making such investigations easier for the end user.

Darktrace/Email indicating a threat across SaaS and email
Figure 2: Darktrace/Email indicating a threat across SaaS and email

What is regulation S-K item 106 of the SEC cybersecurity rules?

The new rules add Item 106 to Regulation S-K requiring registrants to disclose certain information regarding their risk management, strategy, and governance relating to cybersecurity in their annual reports on Form 10-K. The new rules add Item 16K to Form 20-F to require comparable disclosure by [foreign private issuers] in their annual reports on Form 20-F. (6)

SEC cybersecurity rules: Risk management

Specifically, with respect to risk management, Item 106(b) and Item 16K(b) require registrants to describe their processes, if any, for assessing, identifying, and managing material risks from cybersecurity threats, as well as whether any risks from cybersecurity threats, including as a result of any previous cybersecurity incidents, have materially affected or are reasonably likely to materially affect them. The new rules include a non-exclusive list of disclosure items registrants should provide based on their facts and circumstances. (6)

SEC cybersecurity rules: Governance

With respect to governance, Item 106 and Item 16K require registrants to describe the board of directors’ oversight of risks from cybersecurity threats (including identifying any board committee or subcommittee responsible for such oversight) and management’s role in assessing and managing material risks from cybersecurity threats. (6)

How can Darktrace solutions aid in disclosing their risk management, strategy, and governance related to cybersecurity?

Impact scores

Darktrace End-to-End (E2E) leverages AI to understand the complex relationships across users and devices to model possible attack paths, giving security teams a contextual understanding of risk across their digital environments beyond isolated CVEs or CVSS scores. Additionally, teams can prioritize risk management actions to increase their cyber resilience through the E2E Advisory dashboard.

Attack paths consider:

  • Potential damages: Both the potential consequences if a given device was compromised and its immediate implications on other devices.
  • Exposure: Devices' level of interactivity and accessibility. For example, how many emails does a user get via mailing lists and from what kind of sources?
  • Impact: Where a user or asset sits in terms of the IT or business hierarchy and how they communicate with each other. Darktrace can simulate a range of possible outcomes for an uncertain event.
  • Weakness: A device’s patch latency and difficulty, a composite metric that looks at attacker MITRE methods and our own scores to determine how hard each stage of compromise is to achieve.

Because the SEC cybersecurity rules require “oversight of risks from cybersecurity threats” and “management’s role in assessing and managing material risks from cybersecurity threats” (6), the scores generated by Darktrace E2E can aid end-user’s ability to identify risks facing their organization and assign responsibilities to address those risks.

E2E attack paths leverage a deep understanding of a customer’ digital environment and highlight potential attack routes that an attacker could leverage to reach critical assets or entities. Difficulty scores (see Figure 5) allow security teams to measure potential damage, exposure, and impact of an attack on a specific asset or entity.

An example of an attack path in a digital environment
Figure 3: An example of an attack path in a digital environment

Automatic executive threat reports

Darktrace’s solution automatically produces Executive Threat Reports that present a simple visual overview of model breaches (i.e., indicators of unusual and threatening behaviors) and activity in the network environment. Reports can be customized to include extra details or restricted to high level information.

These reports can be generated on a weekly, quarterly, and yearly basis, and can be documented by registrants in relation to Item 106(b) to document parts of their efforts toward assessing, identifying, and managing material risks from cybersecurity threats.

Moreover, Cyber AI Analyst incident reports (described above) can be leveraged to document key details concerning significant previous incidents identified by the Darktrace solution that the registrant determined to be ‘material’.

While the disclosures required by Item 106(c) relate to the governance processes by which the board of directors, the management, and other responsible bodies within an organization oversee risks resulting from cybersecurity threats, the information provided by Darktrace’s Executive Threat Reports and Cyber AI Analyst incident reports can also help relevant stakeholders communicate more effectively regarding the threat landscape and previous incidents.

DISCLAIMER

The material above is provided for informational purposes only. This summary does not constitute legal or compliance advice, recommendations, or guidance. Darktrace encourages you to verify the contents of this summary with your own advisors.

References

  1. Note that the rule does not set forth any specific timeline between the incident and the materiality determination, but the materiality determination should be made without unreasonable delay.
  2. https://www.sec.gov/files/form8-k.pdf
  3. https://www.sec.gov/news/press-release/2023-139
  4. https://www.ecfr.gov/current/title-17/chapter-II/part-229
  5. https://www.sec.gov/files/form8-k.pdf
  6. https://www.sec.gov/corpfin/secg-cybersecurity
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About the author
Kendra Gonzalez Duran
Director of Technology Innovation

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Inside the SOC

Hashing out TA577: Darktrace’s Detection of NTLM Hash Theft

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09
Jul 2024

What is credential theft and how does it work?

What began as a method to achieve unauthorized access to an account, often driven by the curiosity of individual attackers, credentials theft become a key tactic for malicious actors and groups, as stolen login credentials can be abused to gain unauthorized access to accounts and systems. This access can be leveraged to carry out malicious activities such as data exfiltration, fraud, espionage and malware deployment.

It is therefore no surprise that the number of dark web marketplaces selling privileged credentials has increased in recent years, making it easier for malicious actors to monetize stolen credentials [1]. This, in turn, has created new opportunities for threat actors to use increasingly sophisticated tactics such as phishing, social engineering and credential stuffing in their attacks, targeting individuals, organizations and government entities alike [1].

Credential theft example

TA577 Threat Actor

TA577 is a threat actor known to leverage stolen credentials, also known as Hive0118 [2], an initial access broker (IAB) group that was previously known for delivering malicious payloads [2]. On March 4, 2024, Proofpoint reported evidence of TA577 using a new attack chain with a different aim in mind: stealing NT LAN Manager (NTLM) hashes that can be used to authenticate to systems without needing to know plaintext passwords [3].

How does TA577 steal credentials?

Proofpoint reported that this new attack chain, which was first observed on February 26 and 27, was made up of two distinct campaigns. The first campaign consisted of a phishing attack featuring tens of thousands of emails targeting hundreds of organizations globally [3]. These phishing emails often appeared as replies to previous messages (thread hijacking) and contained zipped HTML attachments that each contained a unique file hash, customized for each recipient [3]. These attached files also contained a HTTP Meta refresh function, which triggered an automatic connection to a text file hosted on external IP addresses running as SMB servers [3].

When attempting to access the text file, the server requires an SMB session authentication via NTLM. This session is initiated when a client sends an ‘SMB_COM_NEGOTIATE’ request to the server, which answers with a ‘SMB_COM_NEGOTIATE’ response.

The client then proceeds to send a ‘SMB_COM_SESSION_SETUP_ANDX’ request to start the SMB session setup process, which includes initiating the NTLM authentication process. The server responds with an ‘SMB_COM_SESSION_SETUP_ANDX’ response, which includes an NTLM challenge message [6].

The client can then use the challenge message and its own credentials to generate a response by hashing its password using an NTLM hash algorithm. The response is sent to the server in an ‘SMB_COM_SESSION_SETUP_ANDX’ request. The server validates the response and, if the authentication is successful, the server answers with a final ‘SMB_COM_SESSION_SETUP_ANDX’ response, which completes the session setup process and allows the client to access the file listed on the server [6].

What is the goal of threat actor TA577?

As no malware delivery was detected during these sessions, researchers have suggested that the aim of TA577 was not to deliver malware, but rather to take advantage of the NTLMV2 challenge/response to steal NTLM authentication hashes [3] [4]. Hashes stolen by attackers can be exploited in pass-the-hash attacks to authenticate to a remote server or service [4]. They can also be used for offline password cracking which, if successful, could be utilized to escalate privileges or perform lateral movement through a target network [4]. Under certain circumstances, these hashes could also permit malicious actors to hijack accounts, access sensitive information and evade security products [4].

The open-source toolkit Impacket, which includes modules for password cracking [5] and which can be identified by the default NTLM server challenge “aaaaaaaaaaaaaaaa”[3], was observed during the SMB sessions. This indicates that TA577 actor aim to use stolen credentials for password cracking and pass-the-hash attacks.

TA577 has previously been associated with Black Basta ransomware infections and Qbot, and has been observed delivering various payloads including IcedID, SystemBC, SmokeLoader, Ursnif, and Cobalt Strike [2].This change in tactic to follow the current trend of credential theft may indicate that not only are TA577 actors aware of which methods are most effective in the current threat landscape, but they also have monetary and time resources needed to create new methods to bypass existing detection tools [3].  

Darktrace’s Coverage of TA577 Activity

On February 26 and 26, coinciding with the campaign activity reported by Proofpoint, Darktrace/Email™ observed a surge of inbound emails from numerous suspicious domains targeting multiple customer environments. These emails consistently included zip files with seemingly randomly generated names, containing HTLM content and links to an unusual external IP address [3].

A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace/Email.
Figure 1: A summary of anomaly indicators seen for a campaign email sent by TA577, as detected by Darktrace/Email.
Details of the name and size of the .zip file attached to a campaign email, along with the Darktrace/Email model alerts triggered by the email.
Figure 2: Details of the name and size of the .zip file attached to a campaign email, along with the Darktrace/Email model alerts triggered by the email.

The URL of these links contained an unusually named .txt file, which corresponds with Proofpoint reports of the automatic connection to a text file hosted on an external SMB server made when the attachment is opened [3].

A link to a rare external IP address seen within a campaign email, containing an unusually named .txt file.
Figure 3: A link to a rare external IP address seen within a campaign email, containing an unusually named .txt file.

Darktrace identified devices on multiple customer networks connecting to external SMB servers via the SMB protocol. It understood this activity was suspicious as the SMB protocol is typically reserved for internal connections and the endpoint in question had never previously been observed on the network.

The Event Log of a ‘Compliance / External Windows Communication’ model alert showing a connection to an external SMB server on destination port 445.
Figure 4: The Event Log of a ‘Compliance / External Windows Communication’ model alert showing a connection to an external SMB server on destination port 445.
External Sites Summary highlighting the rarity of the external SMB server.
Figure 5: External Sites Summary highlighting the rarity of the external SMB server.
External Sites Summary highlightin that the SMB server is geolocated in Moldova.
Figure 6: External Sites Summary highlightin that the SMB server is geolocated in Moldova.

During these connections, Darktrace observed multiple devices establishing an SMB session to this server via a NTLM challenge/response, representing the potential theft of the credentials used in this session. During this session, some devices also attempted to access an unusually named .txt file, further indicating that the affected devices were trying to access the .txt file hosted on external SMB servers [3].

Packet captures (PCAPs) of these sessions show the default NTLM server challenge, indicating the use of Impacket, suggesting that the captured NTLM hashes were to be used for password cracking or pass-the-hash-attacks [3]

PCAP analysis showing usage of the default NTLM server challenge associated with Impacket.
Figure 7: PCAP analysis showing usage of the default NTLM server challenge associated with Impacket.

Conclusions

Ultimately, Darktrace’s suite of products effectively detected and alerted for multiple aspects of the TA577 attack chain and NTLM hash data theft activity across its customer base. Darktrace/Email was able to uncover the inbound phishing emails that served as the initial access vector for TA577 actors, while Darktrace DETECT identified the subsequent external connections to unusual external locations and suspicious SMB sessions.

Furthermore, Darktrace’s anomaly-based approach enabled it to detect suspicious TA577 activity across the customer base on February 26 and 27, prior to Proofpoint’s report on their new attack chain. This showcases Darktrace’s ability to identify emerging threats based on the subtle deviations in a compromised device’s behavior, rather than relying on a static list of indicators of compromise (IoCs) or ‘known bads’.

This approach allows Darktrace to remain one step ahead of increasingly adaptive threat actors, providing organizations and their security teams with a robust AI-driven solution able to safeguard their networks in an ever-evolving threat landscape.

Credit to Charlotte Thompson, Cyber Analyst, Anna Gilbertson, Cyber Analyst.

References

1)    https://www.sentinelone.com/cybersecurity-101/what-is-credential-theft/

2)    https://malpedia.caad.fkie.fraunhofer.de/actor/ta577

3)    https://www.proofpoint.com/us/blog/threat-insight/ta577s-unusual-attack-chain-leads-ntlm-data-theft

4)    https://www.bleepingcomputer.com/news/security/hackers-steal-windows-ntlm-authentication-hashes-in-phishing-attacks/

5)    https://pawanjswal.medium.com/the-power-of-impacket-a-comprehensive-guide-with-examples-1288f3a4c674

6)    https://learn.microsoft.com/en-us/openspecs/windows_protocols/ms-nlmp/c083583f-1a8f-4afe-a742-6ee08ffeb8cf

7)    https://www.hivepro.com/threat-advisory/ta577-targeting-windows-ntlm-hashes-in-global-campaigns/

Darktrace Model Detections

Darktrace/Email

·       Attachment / Unsolicited Archive File

·       Attachment / Unsolicited Attachment

·       Link / New Correspondent Classified Link

·       Link / New Correspondent Rare Link

·       Spoof / Internal User Similarities

Darktrace DETECT

·       Compliance / External Windows Communications

Darktrace RESPOND

·       Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

IoCs

IoC - Type - Description

176.123.2[.]146 - IP address -Likely malicious SMB Server

89.117.2[.]33 - IP address - Likely malicious SMB Server

89.117.1[.]161 - IP address - Likely malicious SMB Server

104.129.20[.]167 - IP address - Likely malicious SMB Server

89.117.1[.]160 - IP address - Likely malicious SMB Server

85.239.33[.]149 - IP address - Likely malicious SMB Server

89.117.2[.]34 - IP address - Likely malicious SMB Server

146.19.213[.]36 - IP address - Likely malicious SMB Server

66.63.188[.]19 - IP address - Likely malicious SMB Server

103.124.104[.]76 - IP address - Likely malicious SMB Server

103.124.106[.]224 - IP address - Likely malicious SMB Server

\5aohv\9mn.txt - SMB Path and File - SMB Path and File

\hvwsuw\udrh.txt - SMB Path and File - SMB Path and File

\zkf2rj4\VmD.txt = SMB Path and File - SMB Path and File

\naams\p3aV.txt - SMB Path and File - SMB Path and File

\epxq\A.txt - SMB Path and File - SMB Path and File

\dbna\H.txt - SMB Path and File - SMB Path and File

MAGNAMSB.zip – Filename - Phishing Attachment

e751f9dddd24f7656459e1e3a13307bd03ae4e67 - SHA1 Hash - Phishing Attachment

OMNIS2C.zip  - Filename - Phishing Attachment

db982783b97555232e28d5a333525118f10942e1 - SHA1 Hash - Phishing Attachment

aaaaaaaaaaaaaaaa - NTLM Server Challenge -Impacket Default NTLM Challenge

MITRE ATT&CK Tactics, Techniques and Procedures (TTPs)

Tactic - Technique

TA0001            Initial Access

TA0002            Execution

TA0008            Lateral Movement

TA0003            Persistence

TA0005            Defense Evasion

TA0006            Credential Access

T1021.002       SMB/Windows Admin Shares

T1021  Remote Services

T1566.001       Spearfishing Attachment

T1566  Phishing

T1204.002       Malicious File

T1204  User Execution

T1021.002       SMB/Windows Admin Shares

T1574  Hijack Execution Flow

T1021  Remote Services

T1555.004       Windows Credential Manager

T1555  Credentials from Password Stores

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About the author
Charlotte Thompson
Cyber Analyst
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