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Enhancing Cloud Security with Business Context

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26
Mar 2024
26
Mar 2024
Discover cloud migration insights, security challenges, best practices, and Darktrace's unique approach to enhancing cloud visibility and risk management.

Why are businesses shifting to the cloud?

Businesses are increasingly migrating to cloud, due to its potential to streamline operations, reduce costs, and enhance scalability and flexibility. By shifting their infrastructure to the cloud, either as a whole or, more commonly in a hybrid model, organizations can access a wide array of services, such as storage, compute and software applications, without the need for extensive on-premises hardware. However, this transition isn't without challenges.  

Security challenges of cloud migration

Data security, compliance, integration with existing systems, and ensuring consistent performance are critical concerns that need to be addressed. Therefore, companies must develop robust oversight, implement comprehensive security measures, and invest in staff training to successfully navigate the transition to the cloud all while minimizing potential disruptions.

Implementing security measures within a company, however, is a complex endeavour that involves coordination among numerous internal stakeholders two of the most pivotal players involved in cloud security investment, are the security team, entrusted with crafting a business's defensive strategy, and the DevOps engineering team, architects of the infrastructure underpinning the organization's business operations.

Key questions to ask when securing the cloud

Which team is responsible for maintaining the application?  

What do they consider normal?  

How are potential misconfigurations increasing the potential risk of an incident?

Best practices of cloud security

Contextual awareness of the business is a crucial facet for securing a company's cloud infrastructure, as it enables organizations to align security measures with specific business objectives, risks, and regulatory requirements. Understanding the context of the business operations, its goals, critical assets, and compliance obligations, allows security teams to tailor their strategies and controls accordingly.

How does Darktrace help secure the cloud?

In response to the difficulties outlined above, Darktrace has adopted a holistic approach to security with an ActiveAI security platform that is context-aware. This platform enables stakeholders to effectively detect and respond to threats that may arise within their cloud or on premises environments.  

By monitoring your network and identity activity, Darktrace can identify what is considered “normal” within your organization. This however doesn’t tell the whole story. It is also important to understand where these actions are occurring within the context of the business.  

Visibility in the cloud

Without visibility into the individual assets that make up the cloud environment, how these are configured, and how they operate at run time, security is incredibly difficult to maintain. Visibility allows security teams to identify potential vulnerabilities, misconfigurations, or unauthorized access points that could be exploited by malicious actors. It enables proactive monitoring and rapid response to security incidents, ensuring that any threats are promptly identified and mitigated before they can cause significant damage.  

Building architecture diagrams

The cornerstone of our strategy lies in the architecture diagrams, which serve as a framework for organizing resources within our cloud environment. An architecture comprises of interconnected resources governed by access controls and network routing mechanisms. Its purpose is to logically group these resources into the applications they support.  

Achieving this involves compiling a comprehensive inventory of the cloud environment, analyzing resource permissions—including both outbound and inbound access—and considering any overarching organizational policies. For networked devices, we delve into route tables, firewalls, and subnet access control policies. This information is then utilized to build a graph of interconnected assets, wherein each resource constitutes a node, and the possible connections between resources are represented as edges.

Once we have built up an inventory of all the resources within your environments, we can then start building architectures based on the graph. We do this by selecting distinct starting points for graph traversal, which we infer from our deep understanding of the cloud, an example would be a Virtual Private Cloud (VPC) - A VPC is a virtual network that closely resembles a traditional network that you'd operate in your own data center.  

All networked devices are usually housed within a VPC, with applications typically grouped into one or more VPCs. If multiple VPCs are detected with peering connections between them, we consider them as distinct parts of the same system. This approach enables us to comprehend applications across regions and accounts, rather than solely from the isolated viewpoint of a single VPC.

However, the cloud isn’t all about compute instances, serverless is a popular architecture. In fact, for many developers serverless architectures offer greater scalability and flexibility. Reviewing prevalent serverless architecture patterns, we've chosen some common fundamental resources as our starting point, Lambda functions and Elastic Container Service (ECS) clusters are prime examples, serving as crucial components in various serverless systems with distinct yet similar characteristics.

Prioritize risk in the cloud

Once we have built up an inventory of all the cloud asset, Darktrace/Cloud utilizes an ‘outlier’ detection machine learning model. This looks to categorize all the assets and identifies the ones that look different or ‘odd’ when compared with the assets around it, this is based on a wide range of characteristics some of which will include, Name, VPC ID, Host Region etc, whilst also incorporating contextual knowledge of where these assets are found, and how they fit into the architecture they are in.  

Once outliers are identified, we can use this information to assess the potential risk posed by the asset. Context plays a crucial role in this stage, as incorporating observations about the asset enables effective scoring. For instance, detecting a misconfiguration, anomalous network connections, or unusual user activity can significantly raise the asset's score. Consequently, the architecture it belongs to can be flagged for further investigation.

Adapting to a dynamic cloud environment

The cloud is incredibly dynamic. Therefore, Darktrace does not see architectures as fixed entities. Instead, we're always on the lookout for changes, driven by user and service activity. This prompts us to dive back in, update our architectural view, and keep a living record of the cloud's ever-changing landscape, providing near real-time insights into what's happening within it.  

Darktrace/Cloud doesn’t just consider isolated detections, it identifies assets that have misconfigurations and anomalous activity across the network and management plane and adjusts the priority of the alerting to match the potential risk that these assets could be leveraged to enable an attack.  

While in isolation misconfigurations don’t have much meaningful impact, when they are combined with real time updates and anomaly detection within the context of the architecture you see a very important and impactful perspective.  

Combining all of this into one view where security and dev ops teams can collaborate ensures continuity across teams, playing a vital role in providing effective security.

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.
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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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