Was ist das eigentlich? Cyberrisiken verständlich erklärt

Es wird viel über Cyberrisiken gesprochen. Oftmals fehlt aber das grundsätzliche Verständnis, was Cyberrisiken überhaupt sind. Ohne diese zu verstehen, lässt sich aber auch kein Versicherungsschutz gestalten.

Beinahe alle Aktivitäten des täglichen Lebens können heute über das Internet abgewickelt werden. Online-Shopping und Online-Banking sind im Alltag angekommen. Diese Entwicklung trifft längst nicht nur auf Privatleute, sondern auch auf Firmen zu. Das Schlagwort Industrie 4.0 verheißt bereits eine zunehmende Vernetzung diverser geschäftlicher Vorgänge über das Internet.

Anbieter von Cyberversicherungen für kleinere und mittelständische Unternehmen (KMU) haben Versicherungen die Erfahrung gemacht, dass trotz dieser eindeutigen Entwicklung Cyberrisiken immer noch unterschätzt werden, da sie als etwas Abstraktes wahrgenommen werden. Für KMU kann dies ein gefährlicher Trugschluss sein, da gerade hier Cyberattacken existenzbedrohende Ausmaße annehmen können. So wird noch häufig gefragt, was Cyberrisiken eigentlich sind. Diese Frage ist mehr als verständlich, denn ohne (Cyber-)Risiken bestünde auch kein Bedarf für eine (Cyber-)Versicherung.

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Exam Number : PCPP1
Exam Name : Certified Professional in Python Programming 1 (PCPP)
Vendor Name : Python-Institute
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PCPP1 exam Format | PCPP1 Course Contents | PCPP1 Course Outline | PCPP1 exam Syllabus | PCPP1 exam Objectives


Exam Code: PCPP1
Exam Name: Python-Institute PCPP1 Certified Professional in Python Programming 1 (PCPP)

Module 1: Advanced Object-Oriented Programming (25%)

– Understand and explain the basic terms and programming concepts used in the OOP paradigm
- essential terminology: class, instance, object, attribute, method, type, instance and class variables, superclasses and subclasses
- reflexion: isinstance(), issubclass()
- the __init__() method
- creating classes, methods, and class and instance variables; calling methods; accessing class and instance variables

– Perform Python core syntax operations
- Python core syntax expressions – magic methods: comparison methods (e.g. __eq__(self, other)), numeric methods (e.g. __abs__(self)), type conversion methods (e.g. __init__(self)), object intro- and retrospection (e.g. __str__(self), __instancecheck__(self, object)), object attribute access (e.g. __getattr__(self, attribute)), accessing containers (e.g. __getitem__(self, key))
- operating with special methods
- extending class implementations to support additional core syntax operations

– Understand and use the concepts of inheritance, polymorphism, and composition
- class hierarchies
- single vs. multiple inheritance
- Method Resolution Order (MRO)
- duck typing
- inheritance vs. composition
- modelling real-life problems using the "is a" and "has a" relations

– Understand the concept of extended function argument syntax and demonstrate proficiency in using decorators
- special identifiers: *args, kwargs
- forwarding arguments to other functions
- function parameter handling
- closures
- function and class decorators
- decorating functions with classes
- creating decorators and operating with them: implementing decorator patterns, decorator arguments, wrappers
- decorator stacking
- syntactic sugar
- special methods: __call__, __init__

– Design, build, and use Python static and class methods
- implementing class and static methods
- class vs. static methods
- the cls parameter
- the @classmethod and @staticmethod decorators
- class methods: accessing and modifying the state/methods of a class, creating objects

– Understand and use Python abstract classes and methods
- abstract classes and abstract methods: defining, creating, and implementing abstract classes and abstract methods
- overriding abstract methods
- implementing a multiple inheritance from abstract classes
- delivering multiple child classes

– Understand and use the concept of attribute encapsulation
- definition, meaning, usage
- operating with the getter, setter, and deleter methods

– Understand and apply the concept of subclassing built-in classes
- inheriting properties from built-in classes
- using the concept of subclassing the built-ins to extend class features and modify class methods and attributes

– Demonstrate proficiency in the advanced techniques for creating and serving exceptions
- exceptions as objects, named attributes of exception objects, basic terms and concepts
- chained exceptions, the __context__ and __cause__ attributes, implicitly and explicitly chained exceptions
- analyzing exception traceback objects, the __traceback__ attribute
- operating with different kinds of exceptions

– Demonstrate proficiency in performing shallow and deep copy operations
- shallow and deep copies of objects
- object: label vs. identity vs. value
- the id() function and the is operand
- operating with the copy() and deepcopy() methods

– Understand and perform (de)serialization of Python objects
- object persistence, serialization and deserialization: meaning, purpose, usage
- serializing objects as a single byte stream: the pickle module, pickling various data types
- the MCQs() and loads functions
- serializing objects by implementing a serialization dictionary: the shelve module, file modes, creating chelve objects

– Understand and explain the concept of metaprogramming
- metaclasses: meaning, purpose, usage
- the type metaclass and the type() function
- special attributes: __name__, __class__, __bases__, __dict__
- operating with metaclasses, class variables, and class methods

Module 2: Coding Conventions, Best Practices, and Standardization (12%)

– Understand and explain the concept of Python Enhancement Proposals and Python philosophy
- the PEP concept and selected PEPs: PEP 1, PEP 8, PEP 20, PEP 257
- PEP 1: different types of PEPs, formats, purpose, guidelines
- PEP 20: Python philosophy, its guiding principles, and design; the import this instruction and PEP 20 aphorisms

– Employ the PEP 8 guidelines, coding conventions, and best practices
- PEP 8 compliant checkers
- recommendations for code layout: indentation, continuation lines, maximum line length, line breaks, blank lines (vertical whitespaces)
- default encodings
- module imports
- recommendations for string quotes, whitespace, and trailing commas: single-quoted vs. double-quoted strings, whitespace in expressions and statements, whitespace and trailing commas
- recommendations for using comments: block comments, inline comments
- documentation strings
- naming conventions: naming styles, recommendations
- programming recommendations

– Employ the PEP 257 guidelines, conventions, and best practices
- docstrings: rationale, usage
- comments vs. docstrings
- PEP 484 and type hints
- creating, using, and accessing docstrings
- one-line vs. multi-line docstrings
- documentation standards, linters, fixers

Module 3: GUI Programming (20%)

– Understand and explain the basic concepts and terminology related to GUI programming
- GUI: meaning, rationale, basic terms and definitions
- visual programming: examples, basic features
- widgets/controls – basic terms: windows, title and title bars, buttons, icons, labels, etc.
- classical vs. event-driven programming
- events – basic terms
- widget toolkits/GUI toolkits

– Use GUI toolkits, basic blocks, and conventions to design and build simple GUI applications
- importing tkinter components
- creating an application's main window: the Tk(), mainloop(), and title methods
- adding widgets to the window: buttons, labels, frames, the place() method, widget constructors, location, screen coordinates, size, etc.
- launching the event controller: event handlers, defining and using callbacks, the destroy() method, dialog boxes
- shaping the main window and interacting with the user
- checking the validity of user input and handling errors
- working with Canvas and its methods
- using the Entry, Radiobutton, and Button widgets
- managing widgets with the grid and place managers
- binding events using the bind() method

– Demonstrate proficiency in using widgets and handling events
- settling widgets in the window's interior, geometry managers
- coloring widgets, color modes: RGB, HEX
- event handling: writing event handlers and assigning them to widgets
- event-driven programming: implementing interfaces using events and callbacks
- widget properties and methods
- variables: observable variables and adding observers to variables
- using selected clickable and non-clickable widgets
- identifying and servicing GUI events

Module 4: Network Programming (18%)

– Understand and explain the basic concepts of network programming
- REST
- network sockets
- Domains, addresses, ports, protocols, and services
- Network communication: connection-oriented vs. connectionless communication, clients and servers

– Demonstrate proficiency in working with sockets in Python
- the socket module: importing and creating sockets
- connecting sockets to HTTP servers, closing connections with servers
- sending requests to servers, the send() method
- receiving responses from servers, the recv() method
- exception handling mechanisms and exception types

– Employ data transfer mechanisms for network communication
- JSON: syntax, structure, data types (numbers, strings, Boolean values, null), compound data (arrays and objects), sample JSON documents and their anatomies
- the json module: serialization and deserialization, serializing Python data/deserializing JSON (the MCQs() and loads methods), serializing and deserializing Python objects
- XML: syntax, structure, sample xml documents and their anatomies, DTD, XML as a tree
- processing xml files

– Design, develop, and Boost a simple REST client
- the request module
- designing, building, and using testing environments
- HTTP methods: GET, POST, PUT, DELETE
- CRUD
- adding and updating data
- fetching and removing data from servers
- analyzing the server's response
- response status codes

Module 5: File Processing and Communicating with a Program's Environment (15%)

– Demonstrate proficiency in database programming in Python
- the sqlite module
- creating and closing database connection using the connect and close methods
- creating tables
- inserting, reading, updating, and deleting data
- transaction demarcation
- cursor methods: execute, executemany, fetchone, fetchall
- creating basic SQL statements (SELECT, INSERT INTO, UPDATE, DELETE, etc.)

– Demonstrate proficiency in processing different file formats in Python
- parsing XML documents
- searching data in XML documents using the find and findall methods
- building XML documents using the Element class and the SubElement function
- memorizing and writing CSV data using functions and classes: reader, writer, DictReader, DictWriter
- logging events in applications
- working with different levels of logging
- using LogRecord attributes to create log formats
- creating custom handlers and formatters
- parsing and creating configuration files using the ConfigParser object
- interpolating values in .ini files



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Warum sind Cyberrisiken so schwer greifbar?

Als mehr oder weniger neuartiges Phänomen stellen Cyberrisiken Unternehmen und Versicherer vor besondere Herausforderungen. Nicht nur die neuen Schadenszenarien sind abstrakter oder noch nicht bekannt. Häufig sind immaterielle Werte durch Cyberrisiken in Gefahr. Diese wertvollen Vermögensgegenstände sind schwer bewertbar.

Obwohl die Gefahr durchaus wahrgenommen wird, unterschätzen viele Firmen ihr eigenes Risiko. Dies liegt unter anderem auch an den Veröffentlichungen zu Cyberrisiken. In der Presse finden sich unzählige Berichte von Cyberattacken auf namhafte und große Unternehmen. Den Weg in die Presse finden eben nur die spektakulären Fälle. Die dort genannten Schadenszenarien werden dann für das eigene Unternehmen als unrealistisch eingestuft. Die für die KMU nicht minder gefährlichen Cyber­attacken werden nur selten publiziert.

Aufgrund der fehlenden öffentlichen Meldungen von Sicherheitsvorfällen an Sicherheitsbehörden und wegen der fehlenden Presseberichte fällt es schwer, Fakten und Zahlen zur Risikolage zu erheben. Aber ohne diese Grundlage fällt es schwer, in entsprechende Sicherheitsmaßnahmen zu investieren.

Erklärungsleitfaden anhand eines Ursache-Wirkungs-Modells

Häufig nähert man sich dem Thema Cyberrisiko anlass- oder eventbezogen, also wenn sich neue Schaden­szenarien wie die weltweite WannaCry-Attacke entwickeln. Häufig wird auch akteursgebunden beleuchtet, wer Angreifer oder Opfer sein kann. Dadurch begrenzt man sich bei dem Thema häufig zu sehr nur auf die Cyberkriminalität. Um dem Thema Cyberrisiko jedoch gerecht zu werden, müssen auch weitere Ursachen hinzugezogen werden.

Mit einer Kategorisierung kann das Thema ganzheitlich und nachvollziehbar strukturiert werden. Ebenso hilft eine solche Kategorisierung dabei, eine Abgrenzung vorzunehmen, für welche Gefahren Versicherungsschutz über eine etwaige Cyberversicherung besteht und für welche nicht.

Die Ursachen sind dabei die Risiken, während finanzielle bzw. nicht finanzielle Verluste die Wirkungen sind. Cyberrisiken werden demnach in zwei Hauptursachen eingeteilt. Auf der einen Seite sind die nicht kriminellen Ursachen und auf der anderen Seite die kriminellen Ursachen zu nennen. Beide Ursachen können dabei in drei Untergruppen unterteilt werden.

Nicht kriminelle Ursachen

Höhere Gewalt

Häufig hat man bei dem Thema Cyberrisiko nur die kriminellen Ursachen vor Augen. Aber auch höhere Gewalt kann zu einem empfindlichen Datenverlust führen oder zumindest die Verfügbarkeit von Daten einschränken, indem Rechenzentren durch Naturkatastrophen wie beispielsweise Überschwemmungen oder Erdbeben zerstört werden. Ebenso sind Stromausfälle denkbar.

Menschliches Versagen/Fehlverhalten

Als Cyberrisiken sind auch unbeabsichtigtes und menschliches Fehlverhalten denkbar. Hierunter könnte das versehentliche Veröffentlichen von sensiblen Informationen fallen. Möglich sind eine falsche Adressierung, Wahl einer falschen Faxnummer oder das Hochladen sensibler Daten auf einen öffentlichen Bereich der Homepage.

Technisches Versagen

Auch Hardwaredefekte können zu einem herben Datenverlust führen. Neben einem Überhitzen von Rechnern sind Kurzschlüsse in Systemtechnik oder sogenannte Headcrashes von Festplatten denkbare Szenarien.

Kriminelle Ursachen

Hackerangriffe

Hackerangriffe oder Cyberattacken sind in der Regel die Szenarien, die die Presse dominieren. Häufig wird von spektakulären Datendiebstählen auf große Firmen oder von weltweiten Angriffen mit sogenannten Kryptotrojanern berichtet. Opfer kann am Ende aber jeder werden. Ziele, Methoden und auch das Interesse sind vielfältig. Neben dem finanziellen Interesse können Hackerangriffe auch zur Spionage oder Sabotage eingesetzt werden. Mögliche Hackermethoden sind unter anderem: Social Engineering, Trojaner, DoS-Attacken oder Viren.

Physischer Angriff

Die Zielsetzung eines physischen Angriffs ist ähnlich dem eines Hacker­angriffs. Dabei wird nicht auf die Tools eines Hackerangriffs zurückgegriffen, sondern durch das physische Eindringen in Unternehmensgebäude das Ziel erreicht. Häufig sind es Mitarbeiter, die vertrauliche Informationen stehlen, da sie bereits den notwendigen Zugang zu den Daten besitzen.

Erpressung

Obwohl die Erpressung aufgrund der eingesetzten Methoden auch als Hacker­angriff gewertet werden könnte, ergibt eine Differenzierung Sinn. Erpressungsfälle durch Kryptotrojaner sind eines der häufigsten Schadenszenarien für kleinere und mittelständische Unternehmen. Außerdem sind auch Erpressungsfälle denkbar, bei denen sensible Daten gestohlen wurden und ein Lösegeld gefordert wird, damit sie nicht veröffentlicht oder weiterverkauft werden.

Ihre Cyberversicherung sollte zumindet folgende Schäden abdecken:

Cyber-Kosten:

  • Soforthilfe und Forensik-Kosten (Kosten der Ursachenermittlung, Benachrichtigungskosten und Callcenter-Leistung)
  • Krisenkommunikation / PR-Maßnahmen
  • Systemverbesserungen nach einer Cyber-Attacke
  • Aufwendungen vor Eintritt des Versicherungsfalls

Cyber-Drittschäden (Haftpflicht):

  • Befriedigung oder Abwehr von Ansprüchen Dritter
  • Rechtswidrige elektronische Kommunikation
  • Ansprüche der E-Payment-Serviceprovider
  • Vertragsstrafe wegen der Verletzung von Geheimhaltungspflichten und Datenschutzvereinbarungen
  • Vertragliche Schadenersatzansprüche
  • Vertragliche Haftpflicht bei Datenverarbeitung durch Dritte
  • Rechtsverteidigungskosten

Cyber-Eigenschäden:

  • Betriebsunterbrechung
  • Betriebsunterbrechung durch Ausfall von Dienstleister (optional)
  • Mehrkosten
  • Wiederherstellung von Daten (auch Entfernen der Schadsoftware)
  • Cyber-Diebstahl: elektronischer Zahlungsverkehr, fehlerhafter Versand von Waren, Telefon-Mehrkosten/erhöhte Nutzungsentgelte
  • Cyber-Erpressung
  • Entschädigung mit Strafcharakter/Bußgeld
  • Ersatz-IT-Hardware
  • Cyber-Betrug