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Discord, Telegram, and Slack have all appeared in malware-related activity, but the available evidence does not support naming one the most-used, most covert, or technically superior command-and-control (C2) platform. Reports document Discord and Telegram in C2 and payload delivery, while MITRE documents Discord and Slack in web-service C2 detection guidance and Slack in a 2025 data-exfiltration incident. The practical answer is to investigate context: which process made the connection, which client was used, whether persistence or unusual outbound volume is present, and whether endpoint evidence corroborates compromise.
Which chat platform do malware operators abuse, and how can defenders tell? Treat each service as a possible abuse channel—not as proof of infection. The same destination can represent an employee using an approved app, a browser tab, a software integration, a payload-transfer workflow, or malware hiding in ordinary-looking HTTPS traffic.
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| Name | Best for | Key spec | Checked |
|---|---|---|---|
| Discord | Investigating attachment/CDN abuse and nonstandard clients | Datadog reports C2 and payload-delivery examples; Cisco flags requests made by tools other than the desktop app or a browser | November 2026 |
| Telegram | Investigating API-based C2 and infostealer activity | Datadog reports API use and exfiltration examples; Microsoft observed Telegram C2 in infostealer activity | November 2026 |
| Slack | Hunting web-service C2 and messaging-channel exfiltration | MITRE DET0425 includes Slack in unusual web-service C2 guidance; MITRE records a 2025 Slack-channel exfiltration case | November 2026 |
Is there a single best malware C2 platform?
No. The sources establish observed abuse, not comparative prevalence or a reliable ranking. Datadog discusses Discord and Telegram examples, Cisco provides suspicious-request guidance for Discord and Telegram, and MITRE includes Discord and Slack in detection guidance. Those sources have different scopes—a malware-package study, a network-security reference, a detection strategy, and incident procedure records—so counting their examples would not produce an apples-to-apples risk score.
Chat services are attractive to attackers for a defensive reason: traffic can resemble normal business or personal messaging. That does not make any service inherently malicious, and broad blocking can disrupt legitimate work while failing to address compromised endpoints that can use other channels. A destination-only rule is therefore a weak verdict; process identity, client type, persistence, connection pattern, and data volume carry more investigative value.
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What is the difference between C2, payload delivery, and exfiltration?
They are related but distinct behaviors. Command and control is communication that lets an operator direct an infected system or receive tasking. Payload delivery is the transfer of malware or additional components, such as through an attachment or a service CDN. Exfiltration is the theft of data to an attacker-controlled destination. One campaign can use a service for more than one role, but an indicator for one role should not be presented as proof of all three.
MITRE’s Web Service technique (T1102) describes abuse of web services for command, control, or other communication. Its Messaging Applications technique (T1213.005) addresses obtaining information from messaging repositories, which is a different objective from using a chat service as a C2 transport. Keeping these categories separate prevents an alert about a suspicious outbound request from being overstated as confirmed data theft.
What evidence exists for Discord?
Discord appears in published examples of malware C2 and payload delivery. Datadog Security Labs’ January 10, 2024 article describes malware using Discord-related features, including public attachments and the service’s content-delivery network (CDN). In that context, Discord can be part of communication or a place from which a payload is retrieved; the report does not establish how common the pattern is across all malware.
Cisco’s 2025 Secure Cloud Analytics reference gives a concrete triage clue: a Discord request is more suspicious when it comes from a tool other than the normal desktop application or a browser. Cisco’s guidance is not a declaration that every such request is malicious. Analysts are expected to determine whether the traffic has a legitimate explanation and, if appropriate, quarantine the endpoint.
For defenders, the useful Discord question is not simply “Did the device contact Discord?” Ask which executable opened the connection, whether the user normally uses Discord on that device, whether the request followed a new process or persistence event, and whether attachments or CDN objects were retrieved by an unexpected binary. A browser request from a known user session and a scripted request from a newly dropped executable should not receive the same disposition.
What evidence exists for Telegram?
Datadog reports Telegram API use in malware activity, including examples involving data exfiltration. Microsoft Security’s February 2, 2026 report, “Infostealers without borders”, says its researchers observed Telegram used for C2 in infostealer activity. These findings show that Telegram can be incorporated into malicious workflows; they do not mean that ordinary Telegram application traffic is an infection indicator.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallCisco’s reference also identifies suspicious Telegram requests when a nonstandard tool is responsible. As with Discord, that is a triage signal. Confirm the process, command line, parent process, user, destination details, and timing before escalating. A legitimate automation or approved integration may explain an API connection; an unsigned script launched from a user-writable directory and making repeated outbound requests requires a different response.
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Telegram evidence spans C2 and exfiltration examples, so the same investigation should establish what was actually transferred. Look for request and response sizes, repeated beacon-like timing, file-access events immediately before transmission, and credentials or tokens associated with the process. Do not label a connection “data theft” without evidence that information left the environment.
What evidence exists for Slack?
Slack is represented differently in MITRE’s documentation. MITRE’s DET0425, “Suspicious Use of Web Services for C2,” names Slack alongside Discord and other popular web services when describing unusual outbound connections made by command-line tools, agents, or scripts. This is detection guidance: it tells defenders what behavior to examine, not that every Slack connection is malicious.
MITRE’s Web Service (T1102) procedure examples also include a 2025 Poland Wiper Attacks case in which an attacker-controlled Slack channel was used for data exfiltration. That is evidence of a documented exfiltration incident, not a measured rate of Slack-based C2. It should be kept distinct from DET0425’s broader C2-hunting logic.
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Slack’s heavy use in organizations makes client and process context especially important. A managed desktop client, approved browser session, or sanctioned integration may be normal. A shell, script interpreter, unsigned agent, or newly installed utility making Slack-related outbound connections is the pattern DET0425 is designed to bring to an analyst’s attention.
How should you compare the three services without overstating the evidence?
Use the comparison axes below rather than a league table. Each row describes what the cited evidence supports and what it does not prove.
| Service | Observed role in the available data | Primary evidence | What the evidence cannot establish |
|---|---|---|---|
| Discord | C2 and payload delivery; attachment/CDN use | Datadog examples; Cisco suspicious-request guidance | That Discord is more prevalent or covert than Telegram or Slack |
| Telegram | API-based C2 and exfiltration; infostealer C2 | Datadog examples; Microsoft’s 2026 report; Cisco guidance | That normal Telegram use indicates compromise or that Telegram leads other services |
| Slack | Web-service C2 detection coverage; documented channel exfiltration | MITRE DET0425; MITRE T1102 procedure example | That the cited exfiltration case represents typical Slack usage or prevalence |
The source types are not interchangeable. Datadog’s article is a published threat report, Microsoft’s article reports observations from a specific infostealer investigation, Cisco’s document is an alert reference, and MITRE entries are maintained knowledge-base and detection resources. Different collection methods and reporting biases make a numerical ranking unsound.
What does the 15.7% Datadog figure actually mean?
Datadog Security Labs reported that approximately 15.7% of 1,397 identified malicious PyPI packages used chat-room platforms for C2 or payload delivery. The denominator is the set of malicious packages Datadog identified, not all malware, all Python packages, or all attacks. The figure also combines C2 and payload delivery, which are separate behaviors.
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Use the number to understand that chat-platform abuse can be material in a particular package sample—not to estimate the share of malware using Discord, Telegram, or Slack globally. The article’s author, Andy Giron, wrote that Datadog had “observed numerous malware families leveraging chat platforms for malicious purposes,” and noted that the resources platforms should allocate to monitoring and curbing abuse remain debated. Those statements describe observation and an industry question, not a prevalence ranking.
How do you investigate a suspicious connection to Discord, Telegram, or Slack?
Start with the endpoint and process that made the connection. The destination alone is rarely enough to distinguish a user, an approved integration, and malware.
- Preserve the alert context. Record the timestamp, hostname, user, destination, protocol metadata available to your tools, request or response volume, and the alert rule that fired. Keep the original event so later containment does not erase the timeline.
- Identify the originating process. Map the network event to an executable, process ID, parent process, command line, service account, and file path. Cisco’s nonstandard-client guidance and MITRE DET0425’s focus on command-line tools, agents, and scripts make this step central.
- Classify the client. Determine whether the connection came from the approved desktop application, a browser, a sanctioned integration, or an unusual tool. A browser or managed client may be expected; a newly created script or unsigned binary needs validation.
- Check user and device baseline. Compare the device with its normal software inventory and the user’s normal chat-service use. A developer workstation, build runner, kiosk, and finance laptop can have very different legitimate reasons to contact these services.
- Look for persistence. Review scheduled tasks, services, startup locations, login items, launch agents, run keys, and other persistence telemetry appropriate to the operating system. MITRE’s detection guidance highlights persistence as corroborating context.
- Examine connection patterns. Repeated intervals, unusual destinations or paths, connections shortly after process launch, and traffic continuing when no user session is active can strengthen suspicion. Do not treat any one pattern as conclusive without process and host evidence.
- Measure outbound volume and direction. High or unusual outbound volume can indicate exfiltration, but small command messages can also be C2. Compare bytes sent and received, file events, compression or archiving activity, and the identity of the destination account or channel when your logs expose it.
- Correlate with endpoint activity. Search for credential access, browser-data collection, archive creation, suspicious downloads, defense evasion, or newly written binaries around the same time. A chat connection plus independent compromise indicators is materially stronger than a chat connection alone.
- Validate the business explanation. Contact the service owner, user, or integration owner through a trusted path. Cisco explicitly frames its alert as requiring a legitimacy check; do not quarantine a production workflow solely because a vendor alert names a service.
- Contain proportionally. If evidence supports compromise, isolate the endpoint or restrict the specific process and preserve forensic data. If the activity is legitimate, document the exception, tune the rule, and retain useful telemetry rather than suppressing the entire service.
Which telemetry helps distinguish a normal chat client from malware?
Build a baseline of applications, processes, and devices that normally connect to each service. Useful fields include executable path and hash, signer, parent process, command line, logged-on user, device role, first-seen time, destination details, bytes sent and received, and persistence changes. The goal is to identify deviations without declaring an entire domain unsafe.
Process lineage is often more informative than the hostname. A connection from a known, managed client launched by the expected user is different from a connection made by a shell, script interpreter, temporary executable, office child process, or service account. Alerting can prioritize those combinations while allowing approved applications to continue.
Timing and volume add context. Repeated outbound connections at regular intervals may fit beaconing; a burst after archive creation may fit exfiltration; a one-time download may fit payload delivery. These are hypotheses to test against endpoint records, not verdicts. Record the destination and the behavior that caused concern so investigators can reproduce the reasoning.
Should an organization block Discord, Telegram, or Slack?
Blocking is an organization-specific control decision, not a universal answer. Datadog notes that legitimate chat use can make broad blocking disruptive and potentially ineffective as a sole control. A blanket deny rule may stop an approved collaboration workflow while leaving an infected host able to use another web service or direct connection.
Prefer layered controls where possible: application-aware policies, managed-client allowlists, identity and device controls, endpoint detection, DNS or proxy telemetry, and targeted restrictions on unapproved processes. Restrict high-risk categories or unmanaged clients when business requirements allow, but document exceptions and review them. For a confirmed incident, temporary isolation or a narrow process- or device-level block is usually more informative than permanently denying an entire service to everyone.
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Threat intelligence can guide priority, but it should not replace local context. A service’s appearance in a report means defenders should know how to investigate it; it does not make every connection an indicator of compromise.
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Messaging systems are part of the attack surface even when they are not the C2 transport. MITRE’s T1213.005 guidance supports auditing messaging applications for information that could be exposed or misused. Review who can create channels, invite external participants, generate integrations or webhooks, and retrieve historical data. Apply retention, access, and sensitive-data controls that match your legal and operational requirements.
Maintain a secure out-of-band channel for critical incident communications. MITRE recommends an alternative communication path because an affected collaboration service, compromised account, or attacker-controlled channel may be untrustworthy during response. Keep the alternate method documented, access-controlled, and tested as part of incident-readiness exercises.
During an investigation, avoid posting secrets, malware samples, credentials, or unredacted forensic material into a channel that might be compromised. Use approved evidence storage and verify recipients through a separate trusted path before sharing sensitive findings.
What should a detection rule look for?
A useful rule combines service destination with process and host context. Examples of high-value combinations include:
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- A command-line tool, script, or unknown agent connecting to a chat service for the first time on a device.
- A connection made by a binary launched from a user-writable, temporary, or recently created directory.
- New persistence followed by repeated outbound connections to a chat service.
- Unusual outbound volume, archive creation, or sensitive-file access immediately before the connection.
- Discord or Telegram requests from a nonstandard client where the user and integration owner cannot explain the activity.
- Slack-related connections from a shell or service account that does not normally use Slack.
Rules should emit enough context for triage and should include suppression paths for known-good integrations. A destination-only alert tends to create noise; a process-aware rule can be narrower without ignoring legitimate user activity.
How can teams avoid false positives?
Document approved clients, browser extensions, bots, build systems, ticketing integrations, and automation accounts. Record their owners, expected hosts, normal schedules, and network paths. When an alert fires, compare it with that inventory before escalating.
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Use a graduated response: enrich first, request validation second, isolate when corroborating evidence warrants it. Keep the original event and analyst decision. This preserves a learning loop so recurring legitimate patterns can be tuned while genuinely new process behavior remains visible.
Do not infer compromise from a user’s membership in a server, channel, or group. Investigate the endpoint behavior that produced the network event and whether the account or token was used in an unauthorized way.
What should a practical comparison policy say?
A defensible policy can state that Discord, Telegram, Slack, and similar web services are permitted only through approved clients and integrations where business needs require them; unexpected processes, persistence, or unusual data movement trigger investigation; and confirmed incidents may lead to targeted isolation or blocking. It should also require logging sufficient to map network events to processes and users.
For high-risk environments, add controls for unmanaged devices, external integrations, webhook creation, token storage, and sensitive-data sharing. For developer and automation environments, define explicit exceptions rather than allowing broad, undocumented access. Review the policy when the organization changes collaboration platforms or when threat intelligence identifies a new abuse pattern.
What is the bottom line for defenders?
All three services can be abused, but the evidence supports a defensive comparison—not a ranking. Discord has documented C2 and payload-delivery examples and a nonstandard-client triage signal; Telegram has API, exfiltration, and infostealer-C2 observations; Slack appears in web-service C2 detection guidance and a documented exfiltration incident. None of those facts makes ordinary use suspicious.
Investigate the process, client, persistence, connection pattern, and data volume; corroborate with endpoint evidence; and choose blocking or containment based on business context. Keep sensitive information out of potentially affected channels and maintain an out-of-band incident path so collaboration-service abuse does not disable the response itself.
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Frequently Asked Questions
Can malware use a normal browser session to reach these services?
Yes. A browser can be a legitimate client, but browser-based activity can also be abused through scripts, stolen sessions, or malicious extensions. Check the browser process, extension inventory, account activity, and nearby endpoint events rather than treating browser traffic as automatically safe.
Does using an official Discord, Telegram, or Slack app rule out malware?
No. Malware can coexist with an approved client, abuse an authenticated session, or use a service API separately. The application’s identity is one context signal; process lineage, account behavior, persistence, and data movement still matter.
What evidence is needed before declaring chat-based exfiltration?
You need evidence that data left the endpoint or environment, such as file-access and archive events correlated with outbound bytes, plus destination and account context where available. A connection to a chat service or a high-volume alert alone does not prove that sensitive information was stolen.
How often should collaboration-service access rules be reviewed?
Review them whenever an approved integration, client, or business workflow changes, and after a confirmed incident or material threat report. Keep an owner and an expiration or review date for exceptions so temporary allowances do not become invisible permanent access.
