# tails Published articles for tails. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Behavioral Prior Elicitation via LLM for Heterogeneous-Agent Bitcoin Flash-Crash Simulation DevFeed: [Behavioral Prior Elicitation via LLM for Heterogeneous-Agent Bitcoin Flash-Crash Simulation]() Original publisher: [Read original article]() Author: Tran Phuong Linh Pham, Thi Minh Phuong Ngo, Phuong Thao Nguyen, Quang Minh Nguyen, Thai Hoa Ngo, Trong Nghia Nguyen Published: 2026-11-04T05:00:00Z Content type: article Language: en Sources: [arXiv: Artificial Intelligence]() Topics: [Large Language Model](), [Simulation]() Tags: [bitcoin](), [counterfactual-analysis](), [crash](), [crash-simulation](), [cs-ai](), [flash](), [large](), [large-language-model](), [leverage](), [limit-order-book](), [llm](), [q-fin-tr](), [simulation](), [stat-ap](), [synthetic](), [tails]() ### AI overview The study uses an offline LLM, conditioned on empirical microstructure anchors, to elicit behavioral priors for four agent types in a heterogeneous BTCUSDT limit order book simulator. Its four-stage pipeline builds a 100 ms event panel from 66 detected flash crashes, validates the priors, then uses synthetic simulations for causal discovery and counterfactual analysis. Across 500 runs, LLM-elicited priors yielded a 0.176 crash rate versus 0.008 with uniform priors and produced heavier return tails. In the frozen counterfactual, lowering leverage amplification by one within-sample standard deviation reduced predicted crash rate to 0.136; lowering directional pressure had only a marginal effect. The findings concern a controlled synthetic environment. ### Source excerpt arXiv:2611.03660v1 Announce Type: cross Abstract: Bitcoin perpetual futures trade continuously with shallow liquidity and high price impact, making them prone to millisecond-scale flash crashes. Agent-based limit order book simulators are a natural tool for studying such events, but their behavioral parameters are usually hand-crafted or require full order book histories that are rarely available at scale. We propose a four-stage pipeline that constructs a reproducible 100 ms BTCUSDT flash-crash event panel from 66 detected events, elicits behavioral priors for four agent archetypes using an offline large language model conditioned on empirical microstructure anchors, instantiates a heterogeneous limit order book simulator with the validated priors, and applies causal discovery plus counterfactual analysis to the resulting synthetic panel. Across 500 simulation runs, LLM-elicited priors produce a crash rate of 0.176 versus 0.008 under uninformative uniform priors and generate heav- ier return tails. In the frozen counterfactual analysis, reducing leverage amplification by one within-sample standard deviation lowers the predicted crash rate from 0.176 to 0.136, whereas reducing directional pressure yields only a marginal change. These find- ings suggest that empirically anchored LLM elicitation can improve simulator fidelity and help identify plausible crash-amplification mechanisms in a controlled synthetic environment ## Where Causal Discovery Breaks on Real Data: Measuring the Assumptions One Property at a Time DevFeed: [Where Causal Discovery Breaks on Real Data: Measuring the Assumptions One Property at a Time]() Original publisher: [Read original article]() Author: Padmaja Jonnalagedda, Avinash Baidya, Ruocheng Guo, Kamalika Das Published: 2026-11-03T05:00:00Z Content type: article Language: en Sources: [arXiv: Machine Learning]() Topics: [causality](), [Finance]() Tags: [actions](), [balance-sheet](), [case-study](), [correlation](), [cs-lg](), [discovery](), [flow](), [graph](), [panel](), [power](), [properties](), [revenue](), [sec](), [stat-ml](), [tails]() ### AI overview On a panel of 2,901 US firms across 31 quarters, measurable data problems limit causal discovery, yet the data still contain some information about direct causal pairs. The study finds heavy tails despite winsorisation, near-random-walk behavior in balance-sheet items and revenue, and too little intervention support to detect a 0.1-standard-deviation effect for 40 of 71 corporate actions. A marginal test ranks expert-labelled direct pairs above non-direct pairs within each action (AUROC 0.658), outperforming the study's nulls. At feasible configurations, tuned discovery methods recover less of this signal than pairwise cross-correlation within actions, and no more when ranking within targets. For flow targets, conditioning on other expert-labelled parents weakens marginal discrimination, while most non-direct associations persist. The authors provide diagnostics for assessing each property before running discovery methods. ### Source excerpt arXiv:2611.00484v1 Announce Type: new Abstract: Causal discovery is usually evaluated on simulators or on systems whose ground truth follows from physics or design. When it fails on other real data, the failure is attributed to assumptions that may not hold, but which ones fail, and by how much, is rarely measured. We measure the observable properties of the data they bear on, one property at a time, on a real panel. The case study follows 2,901 US public firms over 31 quarters, with 71 types of corporate action from SEC 8-K filings, 11 financial-statement items, and an expert graph over 651 action-state pairs. The panel breaks measurable requirements of discovery: tails that survive winsorisation, balance-sheet items and revenue close to random walks, and interventions too rare to detect effects of a tenth of a standard deviation in 40 of 71 actions. Even so, a marginal test ranks expert-labelled direct above not-direct pairs within each action (AUROC 0.658) better than every null we built, so the panel does carry information about which pairs are direct. Tuned discovery methods, in configurations feasible at this panel size, recover less of it than a simple pairwise cross-correlation when pairs are ranked within each action, and no more when they are ranked within each target, which removes what the target alone predicts. Most direct pairs (132 of 222) involve actions below the support needed for 80% power against a 0.1-SD effect. For flow targets, conditioning on the target's other expert-labelled parents, often filed alongside the action, erodes the marginal discrimination, and most not-direct associations survive it: even with the graph's parent sets supplied, the expected separation does not emerge. For each property, we give a diagnostic computable before any discovery method is run. ## Heavy-Tailed Memory Traces in Long-Horizon Language Agents DevFeed: [Heavy-Tailed Memory Traces in Long-Horizon Language Agents]() Original publisher: [Read original article]() Author: Xinyuan Song, Zekun Cai Published: 2026-10-30T04:00:00Z Content type: article Language: en Sources: [arXiv: Artificial Intelligence]() Topics: [Artificial Intelligence](), [context window]() Tags: [agent-memory](), [agents](), [budget](), [cs-ai](), [horizon](), [language](), [memory](), [performance](), [policies](), [practical](), [retrieval](), [semantic](), [tails](), [traces]() ### AI overview Repeated retrieval in long-horizon language agents concentrates use on a few memory states, while rarely retrieved states are more prone to prediction errors. A systematic audit found patterns depended on retrieval policy: random walks were compatible with log-normal distributions, while semantic LLM policies produced truncated-power-law-compatible heavy tails. The proposed Core-Tail Memory Controller (CTMC) uses a rank-based prompt budget controlled by one exponent, while retaining summaries of tail information. It reduced memory use while preserving performance on Synthetic Graph World and ALFWorld; on LongMemEval it cut prompt tokens by 24.48% while maintaining aggregate accuracy. ### Source excerpt arXiv:2610.00010v2 Announce Type: replace Abstract: Long-horizon language agents are becoming increasingly important for tasks that require persistent interaction, planning, and reasoning over extended trajectories. External memory plays a central role in these agents by preserving past states, transitions, and experiences beyond the limited context window. Existing memory systems, however, are typically evaluated mainly by task success and token cost, with much less attention to how memory usage is distributed across stored information. We show that repeated retrieval can produce heavy-tailed memory usage, where a small set of states is accessed frequently while many others are rarely retrieved and more prone to prediction errors. We study this phenomenon through a systematic tail audit across retrieval policies and graph structures. We find that memory concentration is reproducible but strongly policy-dependent, ranging from log-normal-compatible patterns under random walks to truncated-power-law-compatible heavy tails under semantic LLM policies. Motivated by these findings, we propose Core-Tail Memory Controller (CTMC), a rank-based memory controller that allocates prompt budget with a single exponent $\tau$ while preserving summarized information from the tail. Across Synthetic Graph World and ALFWorld, CTMC substantially reduces memory usage while preserving performance, and on LongMemEval it reduces prompt tokens by 24.48% while maintaining aggregate accuracy. These results show that heavy-tailed memory usage is both a measurable property of long-horizon agent memory and a practical signal for improving memory efficiency. ## New Release: Tails 7.16 DevFeed: [New Release: Tails 7.16]() Original publisher: [Read original article]() Author: tails Published: 2026-10-30T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [Release notes](), [tor](), [Firefox]() Tags: [browser](), [changes](), [client](), [feedback](), [firefox](), [install](), [installation](), [instructions](), [release](), [releases](), [storage](), [support](), [tails](), [tails-7](), [thunderbird](), [tor](), [update](), [updates](), [upgrade](), [upgrades](), [usb]() ### AI overview Tails 7.16 updates Tor Browser to 16.0, based on Firefox 153 with redesigned settings, and updates the Tor client to 0.4.9.15. It also fixes OpenPGP support in Thunderbird. Automatic upgrades are available from Tails 7.0 or later; if an automatic upgrade is unavailable or Tails fails to start afterward, the release advises trying a manual upgrade. Installing on a new USB stick erases its Persistent Storage, so upgrading is required to keep it. ### Source excerpt Changes and updates Update Tor Browser to 16.0. Tor Browser 16.0 is based on Firefox 153 and inherits its redesigned settings. Update the Tor client to 0.4.9.15. Fixed problems Fix OpenPGP support in Thunderbird. (#21841) Get Tails 7.16 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.16. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.16 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.16 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## New Release: Tails 7.15.1 DevFeed: [New Release: Tails 7.15.1]() Original publisher: [Read original article]() Author: tails Published: 2026-10-23T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [Release notes](), [certificates](), [tor]() Tags: [2026](), [applications](), [attack](), [automatic](), [blocks](), [browser](), [ca](), [certificate](), [certificate-authorities](), [certificate-authority](), [certificates](), [changes](), [cve](), [debian](), [download](), [emergency](), [emudhra](), [release](), [releases](), [tails](), [tails-7]() ### AI overview Tails 7.15.1 is an emergency release that blocks compromised eMudhra certificates. It updates Tor Browser to 15.0.26, which fixes CVE-2026-113470, and updates certificate authorities used by other applications through Debian's `ca-certificates` package. The release says a compromised intermediate certificate could let an attacker impersonate websites over HTTPS; it identifies Tor exit nodes, their internet service providers, or governments as potential attackers. Onion sites are not vulnerable, and the release says it is unaware of exit nodes using the attack so far. Automatic upgrades are available from Tails 7.0 or later. Installing on a new USB stick instead of upgrading erases its Persistent Storage. ### Source excerpt This release is an emergency release to remove a compromised certificate authority. Changes and updates Update Tor Browser to 15.0.26, which fixes CVE-2026-113470. On October 17, Mozilla blocked the certificates of eMudhra, a certificate authority that had its intermediate certificates compromised. Tor Browser 15.0.26 now blocks all eMudhra certificates as well. Using one of the compromised intermediate certificates, an attacker could impersonate any website, even if the connection is secured with HTTPS. This attack could be performed by a Tor exit node, the Internet service provider of an exit node, or a government. Onion sites are not vulnerable. We are not aware of this attack being used by exit nodes so far. Update the certificate authorities to block all eMudhra certificates in other applications. In addition to Tor Browser , other applications rely on the certificate authorities included in Tails with the ca-certificates Debian package to secure their connections. Get Tails 7.15.1 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.15.1. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.15.1 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.15.1 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## Weak-$L^\\alpha$ Noise, Strong Guarantees: Gradient Clipping under Affine Heavy Tails DevFeed: [Weak-$L^\\alpha$ Noise, Strong Guarantees: Gradient Clipping under Affine Heavy Tails]() Original publisher: [Read original article]() Author: Alyona Nekrasova, Makar Sidorov, Savelii Chezhegov, Alexander Gasnikov, Margarita Preobrazhenskaia, Igor Preobrazhensky, Eduard Gorbunov Published: 2026-10-21T04:00:00Z Content type: article Language: en Sources: [arXiv: Machine Learning]() Topics: [Combinatorial optimization]() Tags: [accelerated](), [clipping](), [cs-lg](), [experiments](), [gradient](), [guarantees](), [lower-bounds](), [math-oc](), [noise](), [optimization](), [tails]() ### AI overview For smooth convex optimization with affine heavy-tailed noise, clipped SGD (Clip-SGD) and accelerated Clip-SSTM obtain high-probability convergence guarantees under a weak-L^α tail condition, which is weaker than the corresponding bounded-moment assumption. For 1<α<2, both achieve additive stochastic error of order K^{-(α−1)/α}; gradient-dependent noise decays faster, at K^{-2(α−1)/α} up to logarithmic factors. At α=2, the paper characterizes an additional Lorentz-scale logarithmic factor and shows it is necessary for additive error at fixed confidence. It also gives finite-horizon guarantees for prescribed Clip-SGD clipping levels, with convergence to a clipping-bias neighborhood; for additive noise, matching lower bounds establish that this neighborhood is unavoidable up to constants and a natural error cap. Pareto-noise experiments illustrate the theory. ### Source excerpt arXiv:2610.28107v1 Announce Type: cross Abstract: Gradient clipping is a key tool for obtaining high-probability convergence guarantees for stochastic first-order methods under heavy-tailed noise. Existing analyses typically assume a bounded central moment of order $\alpha\in(1,2]$, which excludes distributions with tails of order $u^{-\alpha}$ at the critical exponent. In this paper, we consider smooth convex optimization under affine heavy-tailed noise, whose scale may grow with the gradient norm. We derive high-probability convergence guarantees for clipped SGD (Clip-SGD) and its accelerated variant Clip-SSTM under a weak-$L^\alpha$ tail condition, which is strictly weaker than the corresponding moment bound. For $1<\alpha<2$, the clipping bounds have the same powers of the clipping level as in the moment case, and both methods attain the additive stochastic rate $K^{-(\alpha-1)/\alpha}$. The gradient-dependent noise contributes a faster-decaying term of order $K^{-2(\alpha-1)/\alpha}$, up to logarithmic factors. At $\alpha=2$, we characterize the additional logarithmic factor on the Lorentz scale and establish its necessity for the additive error at fixed confidence. We also analyze Clip-SGD with prescribed clipping levels and derive finite-horizon guarantees for reaching a neighborhood determined by the clipping bias. For additive noise, matching lower bounds show that this neighborhood is unavoidable, up to constants and the natural error cap. Numerical experiments with Pareto noise illustrate the theoretical results. ## New Release: Tails 7.15 DevFeed: [New Release: Tails 7.15]() Original publisher: [Read original article]() Author: tails Published: 2026-10-13T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [firmware-update]() Tags: [firmware](), [hardware](), [install](), [packages](), [release](), [releases](), [storage](), [tails](), [tails-7](), [tor](), [update](), [usb](), [virtual-machines](), [wi-fi]() ### AI overview Tails 7.15 updates Tor Browser to 15.0.25, the Tor client to 0.4.9.14, and firmware packages to improve support for newer hardware. The release provides automatic upgrades from Tails 7.0 or later, manual upgrade guidance, and installation and download options. ### Source excerpt Changes and updates Update Tor Browser to 15.0.25. Update the Tor client to 0.4.9.14. Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on. Get Tails 7.15 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.15. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.15 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.15 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## New Release: Tails 7.14 DevFeed: [New Release: Tails 7.14]() Original publisher: [Read original article]() Author: tails Published: 2026-09-30T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [Linux]() Tags: [kernel](), [keyboard](), [release](), [releases](), [tails](), [tails-7](), [update]() ### AI overview Tails 7.14 updates Tor Browser, the Tor client, and the Linux kernel, and fixes the default keyboard input method when starting a session in Korean. Automatic upgrades are available from Tails 7.0 or later; the post also provides manual upgrade and installation guidance. ### Source excerpt Changes and updates Update Tor Browser to 15.0.24. Update the Tor client to 0.4.9.13. Update the Linux kernel to 6.12.111. Fixed problems Fix the default keyboard input method when starting a session in Korean. (#21779) Get Tails 7.14 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.14. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.14 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.14 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## New Release: Tails 7.13 DevFeed: [New Release: Tails 7.13]() Original publisher: [Read original article]() Author: tails Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [USB](), [ZeroNet](), [virtual machines](), [browser]() Tags: [browser](), [download](), [release](), [releases](), [tails](), [tails-7](), [tails-7-13](), [tor](), [update](), [updates](), [upgrade](), [upgrades](), [usb](), [virtual-machines]() ### AI overview Tails 7.13 updates Tor Browser to 15.0.23 and the Tor client to 0.4.9.12, and simplifies shutdown by removing the Power Off dialog when no application or document requires confirmation. The release supports automatic or manual upgrades and installation on USB sticks, DVDs, and virtual machines. ### Source excerpt Changes and updates Update Tor Browser to 15.0.23. Update the Tor client to 0.4.9.12. Simplify the shutdown procedure. Since Tails 7.10, you had to confirm shutting down in a Power Off dialog. For faster shutdowns, we removed this dialog when no application needs to be closed and no document needs to be saved before shutting down. Get Tails 7.13 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.13. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.13 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.13 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## New Release: Tails 7.12 DevFeed: [New Release: Tails 7.12]() Original publisher: [Read original article]() Author: tails Published: 2026-09-03T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [Firefox](), [Hardware]() Tags: [firefox](), [firmware](), [hardware](), [release](), [releases](), [tails](), [tails-7](), [updates](), [upgrade](), [usb]() ### AI overview Tails 7.12 is the first release in a new two-week release cadence aligned with Firefox and Tor Browser. It updates Electrum, Tor Browser, and firmware packages, with automatic upgrades available for supported Tails versions. ### Source excerpt Firefox is moving to a 2-week release cadence starting in September, and so Tor Browser and Tails are doing the same. Tails 7.12 is the first release on this new cadence. Changes and updates Update Electrum from 4.7.2 to 4.8.1. Update Tor Browser to 15.0.21. Update some firmware packages. This improves support for newer hardware, including graphics cards, Wi-Fi, and more. Get Tails 7.12 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.12. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.12 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.12 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## New Release: Tails 7.11 DevFeed: [New Release: Tails 7.11]() Original publisher: [Read original article]() Author: tails Published: 2026-08-19T00:00:00Z Content type: release Language: en Sources: [Tor Project]() Topics: [releases](), [upgrade](), [USB](), [tor](), [virtual machines](), [Disk image]() Tags: [browser](), [changelog](), [download](), [image](), [install](), [installation](), [iso](), [release](), [releases](), [tails](), [tails-7](), [tor](), [update](), [upgrade](), [usb](), [virtual-machines]() ### AI overview Tails 7.11 updates Tor Browser to version 15.0.20 and fixes activation of Persistent Storage on some computers. The release provides automatic and manual upgrade guidance, installation options for USB sticks, and downloads for USB images, DVDs, and virtual machines. ### Source excerpt Changes and updates Update Tor Browser to 15.0.20. Fixed problems Fix activation of Persistent Storage on some computers. (#19913) For more details, read our changelog. Get Tails 7.11 To upgrade your Tails USB stick and keep your Persistent Storage Automatic upgrades are available from Tails 7.0 or later to 7.11. If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade. To install Tails 7.11 on a new USB stick Follow our installation instructions. The Persistent Storage on the USB stick will be lost if you install instead of upgrading. To download only If you don't need installation or upgrade instructions, you can download Tails 7.11 directly: For USB sticks (USB image) For DVDs and virtual machines (ISO image) Support and feedback For support and feedback, visit the Support section on the Tails website. tails releases ## Using OpenTofu/Terraform to create a disposable Tails virtual machine DevFeed: [Using OpenTofu/Terraform to create a disposable Tails virtual machine]() Original publisher: [Read original article]() Author: Staf Wagemakers Published: 2025-06-22T06:37:00Z Content type: tutorial Language: en Sources: [stafwag]() Topics: [opentofu](), [Infrastructure as code](), [virtualization](), [Linux]() Tags: [fosdem](), [infrastructure-as-code](), [libvirt](), [linux](), [linux-foundation](), [open-source](), [opentofu](), [tails](), [terraform](), [tor](), [virtual-machine](), [virtualization]() ### AI overview This tutorial explains how OpenTofu and Terraform can provision disposable environments and presents a Terraform/OpenTofu module for creating a virtual machine running the latest Tails version on libvirt. It also notes security considerations for running Tails in a virtual machine. ### Source excerpt OpenTofu Terraform or OpenTofu (the open-source fork supported by the Linux Foundation) is a nice tool to setup the infrastructure on different cloud environments. There is also a provider that supports libvirt. https://github.com/dmacvicar/terraform-provider-libvirt If you want to get started with OpenTofu there is a free training available from the Linux foundation: https://training.linuxfoundation.org/express-learning/getting-started-with-opentofu-lfel1009/ I also joined the talk about OpenTofu and Infrastructure As Code, in general, this year in the Virtualization and Cloud Infrastructure DEV Room at FOSDEM this year: https://fosdem.org/2025/schedule/event/fosdem-2025-6057-the-iac-tooling-multiverse-and-the-future-of-iac/ ## Tails installer is now in Debian DevFeed: [Tails installer is now in Debian]() Original publisher: [Read original article]() Author: u Published: 2016-02-11T13:30:00Z Content type: release Language: en Sources: [Bits from Debian]() Topics: [Debian](), [Digital Security](), [Linux](), [Security](), [USB](), [Persistence]() Tags: [2016](), [announce](), [anonymity](), [debian](), [digital-security](), [encrypted](), [installer](), [iso](), [persistence](), [privacy](), [tails](), [usb]() ### AI overview Tails Installer has been added to Debian as a graphical tool for installing or upgrading Tails on USB devices from an ISO image. It simplifies the setup process and supports encrypted persistent storage for personal files and settings. ### Source excerpt Tails (The amnesic incognito live system) is a live OS based on Debian GNU/Linux which aims at preserving the user's privacy and anonymity by using the Internet anonymously and circumventing censorship. Installed on a USB device, it is configured to leave no trace on the computer you are using unless asked explicitly. As of today, the people the most needy for digital security are not computer experts. Being able to get started easily with a new tool is critical to its adoption, and even more in high-risk and stressful environments. That's why we wanted to make it faster, simpler, and more secure to install Tails for new users. One of the components of Tails, the Tails Installer is now in Debian thanks to the Debian Privacy Tools Maintainers Team. Tails Installer is a graphical tool to install or upgrade Tails on a USB stick from an ISO image. It aims at making it easier and faster to get Tails up and running. The previous process for getting started with Tails was very complex and was problematic for less tech-savvy users. It required starting Tails three times, and copying the full ISO image onto a USB stick twice before having a fully functional Tails USB stick with persistence enabled. This can now be done simply by installing Tails Installer in your existing Debian system, using sid, stretch or jessie-backports, plugging a USB stick and choosing if one wants to update the USB stick or to install Tails using a previously downloaded ISO image. Tails Installer also helps Tails users to create an encrypted persistent storage for personal files and settings in the rest of the available space.