| REC-0001 |
Gather Spacecraft Design Information |
Threat actors seek a coherent picture of the spacecraft and its supporting ecosystem to reduce uncertainty and plan follow-on actions. Useful design information spans avionics architecture, command and data handling, comms and RF chains, power and thermal control, flight dynamics constraints, payload-to-bus interfaces, redundancy schemes, and ground segment dependencies. Artifacts often include ICDs, block diagrams, SBOMs and toolchains, test procedures, AIT travelers, change logs, and “as-built” versus “as-flown” deltas. Adversaries combine open sources (papers, patents, theses, conference slides, procurement documents, FCC/ITU filings, marketing sheets) with gray sources (leaked RFP appendices, vendor manuals, employee resumes, social posts) to infer single points of failure, unsafe modes, or poorly defended pathways between space, ground, and supply chain. The output of this activity is not merely a document set but a working mental model and, often, a lab replica that enables rehearsal, timing studies, and failure-mode exploration. |
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REC-0001.01 |
Software Design |
Adversaries target knowledge of flight and ground software to identify exploitable seams and to build high-fidelity emulators for rehearsal. Valuable details include RTOS selection and version, process layout, inter-process messaging patterns, memory maps and linker scripts, fault-detection/isolation/recovery logic, mode management and safing behavior, command handlers and table services, bootloaders, patch/update mechanisms, crypto libraries, device drivers, and test harnesses. Artifacts may be source code, binaries with symbols, stripped images with recognizable patterns, configuration tables, and SBOMs that reveal vulnerable dependencies. With these, a threat actor can reverse engineer command parsing, locate debug hooks, craft inputs that bypass FDIR, or time payload and bus interactions to produce cascading effects. Supply-chain access to vendors of COTS components, open-source communities, or integrators can be used to insert weaknesses or to harvest build metadata. Even partial disclosures, such as a unit test name, an assert message, or a legacy API, shrink the search space for exploitation. |
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REC-0001.02 |
Firmware |
Firmware intelligence covers microcontroller images, programmable logic bitstreams, boot ROM behavior, peripheral configuration blobs, and anti-rollback or secure-boot settings for devices on the bus. Knowing device types, versions, and footprints enables inference of default passwords, debug interfaces (JTAG, SWD, UART), timing tolerances, and error handling under brownout or thermal stress. A threat actor may obtain firmware from vendor reference packages, public evaluation boards, leaked manufacturing files, over-the-air update images, or crash dumps. Correlating that with board layouts, harness drawings, or part markings helps map trust boundaries and locate choke points like power controllers, bus bridges, and watchdog supervisors. Attack goals include: preparing malicious but apparently valid updates, exploiting unsigned or weakly verified images, forcing downgrades, or manipulating configuration fuses to weaken later defenses. Even when cryptographic verification is present, knowledge of recovery modes, boot-pin strapping, or maintenance commands can offer alternate paths. |
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REC-0001.03 |
Cryptographic Algorithms |
Adversaries look for the complete crypto picture: algorithms and modes, key types and lifecycles, authentication schemes, counter or time-tag handling, anti-replay windows, link-layer protections, and any differences between uplink and downlink policy. With algorithm and key details, a threat actor can craft valid telecommands, masquerade as a trusted endpoint, or degrade availability through replay and desynchronization. Sources include interface specifications, ground software logs, test vectors, configuration files, contractor laptops, and payload-specific ICDs that reuse bus-level credentials. Particular risk arises when command links rely on authentication without confidentiality; once an adversary acquires the necessary keys or counters, they can issue legitimate-looking commands outside official channels. Programs should assume that partial disclosures, MAC length, counter reset rules, or key rotation cadence, aid exploitation. |
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REC-0001.04 |
Data Bus |
Bus intelligence focuses on which protocols are used (e.g., MIL-STD-1553, SpaceWire, etc.), controller roles, addressing, timings, arbitration, redundancy management, and the location of critical endpoints on each segment. Knowing the bus controller, remote terminal addresses, message identifiers, and schedule tables allows an adversary to craft frames that collide with or supersede legitimate traffic, to starve health monitoring, or to trigger latent behaviors in payload or power systems. Additional details such as line voltages, termination, connector types, harness pinouts, and EMC constraints inform feasibility of injection and disruption techniques. Attackers assemble this picture from ICDs, vendor datasheets, AIT procedures, harness drawings, lab photos, and academic or trade publications that reveal typical configurations. Enumeration of bridges and gateways is especially valuable because they concentrate trust across fault-containment regions and between payload and bus. |
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REC-0001.05 |
Thermal Control System |
Adversaries seek a working map of the thermal architecture and its operating envelopes to anticipate stress points and plan timing for other techniques. Valuable details include passive elements (MLI, coatings, radiators, heat pipes/straps, louvers) and active control (survival and control heaters, thermostats, pumped loops), plus sensor placement, setpoints, deadbands, heater priority tables, and autonomy rules that protect critical hardware during eclipses and anomalies. Artifacts often come from thermal math models (TMMs), TVAC test reports, heater maps and harness drawings, command mnemonics, and on-orbit thermal balance procedures. When correlated with attitude constraints, payload duty cycles, and power budgets, this information lets a threat actor infer when components run close to limits, how safing responds to off-nominal gradients, and where power-thermal couplings can be exploited. Even small fragments, such as louver hysteresis or a heater override used for decontamination, can reveal opportunities to mask heating signatures or provoke nuisance safing. |
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REC-0001.06 |
Maneuver & Control |
Threat actors collect details of the guidance, navigation, and control (GNC) stack to predict vehicle response and identify leverage points during station-keeping, momentum management, and anomaly recovery. Useful specifics include propulsion type and layout (monoprop/biprop/electric; thruster locations, minimum impulse bit, plume keep-out zones), reaction wheels/CMGs and desaturation logic, control laws and gains, estimator design (e.g., EKF), timing and synchronization, detumble/safe-mode behaviors, and the full sensor suite (star trackers, sun sensors, gyros/IMUs, GNSS). Artifacts include AOCS/AOCS ICDs, maneuver procedures, delta-v budgets, ephemeris products, scheduler tables, and wheel management timelines. Knowing when and how attitude holds, acquisition sequences, or wheel unloads occur helps an adversary choose windows where injected commands or bus perturbations have outsized effect, or where sensor blinding and spoofing are most disruptive. |
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REC-0001.07 |
Payload |
Adversaries pursue a clear picture of payload type, operating modes, command set, and data paths to and from the bus and ground. High-value details include vendor and model, operating constraints (thermal, pointing, contamination), mode transition logic, timing of calibrations, safety inhibits and interlocks, firmware/software update paths, data formatting and compression, and any crypto posture differences between payload links and the main command link. Payload ICDs often reveal addresses, message identifiers, and gateway locations where payload traffic bridges to the C&DH or data-handling networks, creating potential pivot points. Knowledge of duty cycles and scheduler entries enables timing attacks that coincide with high-power or high-rate operations to stress power/thermal margins or saturate storage and downlink. Even partial information, calibration script names, test vectors, or engineering telemetry mnemonics, can shrink the search space for reverse engineering. |
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REC-0001.08 |
Power |
Reconnaissance of the electrical power system (EPS) focuses on generation, storage, distribution, and autonomy. Useful details include solar array topology and SADA behavior, MPPT algorithms, array string voltages, eclipse depth assumptions, battery chemistry and configuration, BMS charge/discharge limits and thermal dependencies, PCDU architecture, load-shed priorities, latching current limiters, and survival power rules. Artifacts surface in EPS ICDs, acceptance test data, TVAC power margin reports, anomaly response procedures, and vendor manuals. Correlating these with attitude plans and payload schedules lets a threat actor infer when state-of-charge runs tight, which loads are shed first, and how fast recovery proceeds after a brownout or safing entry. Knowledge of housekeeping telemetry formats and rate caps helps identify blind spots where abusive load patterns or command sequences may evade detection. |
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REC-0001.09 |
Fault Management |
Fault management (FDIR/autonomy/safing) materials are a prime reconnaissance target because they encode how the spacecraft detects, classifies, and responds to off-nominal states. Adversaries seek trigger thresholds and persistence timers, voting logic, inhibit and recovery ladders, safe-mode entry/exit criteria, command authority in safed states, watchdog/reset behavior, and any differences between flight and maintenance builds. Artifacts include fault trees, FMEAs, autonomy rule tables, safing flowcharts, and anomaly response playbooks. With these, a threat actor can craft inputs that remain just below detection thresholds, stack benign-looking events to cross safing boundaries at tactically chosen times, or exploit recovery windows when authentication, visibility, or redundancy is reduced. Knowledge of what telemetry is suppressed or rate-limited during safing further aids concealment. |
| REC-0003 |
Gather Spacecraft Communications Information |
Threat actors assemble a detailed picture of the mission’s RF and networking posture across TT&C and payload links. Useful elements include frequency bands and allocations, emission designators, modulation/coding, data rates, polarization sense, Doppler profiles, timing and ranging schemes, link budgets, and expected Eb/N0 margins. They also seek antenna characteristics, beacon structures, and whether transponders are bent-pipe or regenerative. On the ground, they track station locations, apertures, auto-track behavior, front-end filters/LNAs, and handover rules, plus whether services traverse SLE, SDN, or commercial cloud backbones. Even small details, polarization sense, roll-off factors, or beacon cadence, shrink the search space for interception, spoofing, or denial. The outcome is a lab-replicable demod/decode chain and a calendar of advantageous windows. |
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REC-0003.01 |
Communications Equipment |
Adversaries inventory space and ground RF equipment to infer capabilities, limits, and attack surfaces. On the spacecraft, they seek antenna type and geometry, placement and boresight constraints, polarization, RF front-end chains, transponder type, translation factors, gain control, saturation points, and protective features. On the ground, they collect dish size/aperture efficiency, feed/polarizer configuration, tracking modes, diversity sites, and backend modem settings. Beacon frequency/structure, telemetry signal type, symbol rates, and framing reveal demodulator parameters and help an actor build compatible SDR pipelines. Knowledge of power budgets and AGC behavior enables strategies to push hardware into non-linear regimes, causing self-inflicted denial or intermodulation. Equipment location and mounting inform visibility and interference opportunities. |
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REC-0003.02 |
Commanding Details |
Threat actors study how commands are formed, authorized, scheduled, and delivered. High-value details include the telecommand protocol (e.g., CCSDS TC), framing and CRC/MAC fields, authentication scheme (keys, counters, anti-replay windows), command dictionary/database formats, critical-command interlocks and enable codes, rate and size limits, timetag handling, command queue semantics, and the roles of scripts or procedures that batch actions. They also collect rules governing “valid commanding periods”: line-of-sight windows, station handovers, maintenance modes, safing states, timeouts, and when rapid-response commanding is permitted. With this, an adversary can craft syntactically valid traffic, time injections to coincide with reduced monitoring, or induce desynchronization (e.g., counter resets, stale timetags). |
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REC-0003.03 |
Mission-Specific Channel Scanning |
Beyond TT&C, many missions expose additional RF or network surfaces: high-rate payload downlinks (e.g., X/Ka-band), user terminals, inter-satellite crosslinks, and hosted-payload channels that may be operated by different organizations. Adversaries scan spectrum and public telemetry repositories for these mission-specific channels, characterizing carrier plans, burst structures, access schemes (TDMA/FDMA/CDMA), addressing, and gateway locations. For commercial services, they enumerate forward/return links, user terminal waveforms, and provisioning backends that could be impersonated or jammed selectively. In hosted-payload or rideshare contexts, differences in configuration control and key management present opportunities for pivoting between enclaves. |
| REC-0004 |
Gather Launch Information |
Adversaries collect structured launch intelligence to forecast when and how mission assets will transition through their most time-compressed, change-prone phase. Useful elements include the launch date/time windows, launch site and range operator, participating organizations (launch provider, integrator, range safety, telemetry networks), vehicle family and configuration, fairing type, and upper-stage restart profiles. This picture enables realistic social-engineering pretexts, supply-chain targeting of contractors, and identification of auxiliary systems (range instrumentation, TLM/FTS links) that may be less hardened than the spacecraft itself. Knowledge of ascent comms (bands, beacons, ground stations), early-orbit operations (LEOP) procedures, and handovers to mission control further informs when authentication, staffing, or telemetry margins may be tight. |
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REC-0004.01 |
Flight Termination |
Threat actors may attempt to learn how the launch vehicle’s flight termination capability is architected and governed, command-destruct versus autonomous flight termination (AFTS), authority chains, cryptographic protections, arming interlocks, inhibit ladders, telemetry indicators, and range rules for safe-flight criteria. While FTS is a range safety function, its interfaces (command links, keys, timing sources, decision logic) can reveal design patterns, dependencies, and potential misconfigurations across the broader launch ecosystem. Knowledge of test modes, simulation harnesses, and pre-launch checks could inform social-engineering or availability-degrading actions against range or contractor systems during critical windows. |
| REC-0009 |
Gather Mission Information |
Adversaries compile a CONOPS-level portrait of the mission to predict priorities, constraints, and operational rhythms. They harvest stated needs, goals, and performance measures; enumerate key elements/instruments and their duty cycles; and extract mode logic, operational constraints (pointing, keep-outs, contamination, thermal/power margins), and contingency concepts. They mine the scientific and engineering basis, papers, algorithms, calibration methods, to anticipate data value, processing chains, and where integrity or availability attacks would have maximal effect. They correlate physical and support environments (ground networks, cloud pipelines, data distribution partners, user communities) and public schedules (campaigns, calibrations, maneuvers) to identify periods of elevated workload or reduced margin. The aim is not merely understanding but timing: choosing moments when authentication might be relaxed, monitoring is saturated, or rapid-response authority is invoked. |